2.2 EEG DL Classification.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d4809c9f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "physical_devices = tf.config.list_physical_devices('GPU')\n",
    "tf.config.experimental.set_memory_growth(physical_devices[0], enable=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9c4a3bc5",
   "metadata": {},
   "outputs": [],
   "source": [
    "from glob import glob\n",
    "import os\n",
    "import mne\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2b11214d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "28\n"
     ]
    }
   ],
   "source": [
    "#read all file\n",
    "all_files_path=glob('dataverse_files/*.edf')\n",
    "print(len(all_files_path))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3126e54c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'dataverse_files\\\\h01.edf'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_files_path[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7bd827d0",
   "metadata": {},
   "outputs": [],
   "source": [
    "healthy_file_path=[i for i in all_files_path if  'h' in i.split('\\\\')[1]]\n",
    "patient_file_path=[i for i in all_files_path if  's' in i.split('\\\\')[1]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1d84e167",
   "metadata": {},
   "outputs": [],
   "source": [
    "def read_data(file_path):\n",
    "    datax=mne.io.read_raw_edf(file_path,preload=True)\n",
    "    datax.set_eeg_reference()\n",
    "    datax.filter(l_freq=1,h_freq=45)\n",
    "    epochs=mne.make_fixed_length_epochs(datax,duration=25,overlap=0)\n",
    "    epochs=epochs.get_data()\n",
    "    return epochs #trials,channel,length"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b1352819",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\h01.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 231249  =      0.000 ...   924.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "37 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 37 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n"
     ]
    }
   ],
   "source": [
    "data=read_data(healthy_file_path[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a48348ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(37, 19, 6250)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e6aea13c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\h01.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 231249  =      0.000 ...   924.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "37 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 37 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n",
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\h02.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 227499  =      0.000 ...   909.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "36 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 36 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n",
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\h03.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 227499  =      0.000 ...   909.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "36 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 36 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n",
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\h04.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 231249  =      0.000 ...   924.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "37 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 37 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n",
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\h05.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 236249  =      0.000 ...   944.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "37 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 37 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n",
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\h06.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 232499  =      0.000 ...   929.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "37 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 37 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n",
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\h07.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 227499  =      0.000 ...   909.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "36 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 36 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n",
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\h08.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 227499  =      0.000 ...   909.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "36 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 36 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n",
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\h09.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 226249  =      0.000 ...   904.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "36 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 36 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n",
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\h10.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 278749  =      0.000 ...  1114.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "44 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 44 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n",
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\h11.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 228749  =      0.000 ...   914.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "36 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 36 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n",
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\h12.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 224999  =      0.000 ...   899.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "36 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 36 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n",
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\h13.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 241249  =      0.000 ...   964.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "38 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 38 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n",
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\h14.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 216249  =      0.000 ...   864.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "34 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 34 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n",
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\s01.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 211249  =      0.000 ...   844.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "33 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 33 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n",
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\s02.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 286249  =      0.000 ...  1144.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "45 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 45 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n",
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\s03.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 240999  =      0.000 ...   963.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "38 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 38 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n",
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\s04.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 301249  =      0.000 ...  1204.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "48 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 48 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n",
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\s05.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 222499  =      0.000 ...   889.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "35 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 35 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n",
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\s06.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 184999  =      0.000 ...   739.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "29 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 29 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n",
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\s07.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 336499  =      0.000 ...  1345.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "53 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 53 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n",
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\s08.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 227749  =      0.000 ...   910.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "36 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 36 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n",
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\s09.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading 0 ... 296249  =      0.000 ...  1184.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "47 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 47 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n",
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\s10.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 212499  =      0.000 ...   849.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "34 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 34 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n",
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\s11.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 339999  =      0.000 ...  1359.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "54 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 54 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n",
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\s12.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 271749  =      0.000 ...  1086.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "43 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 43 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n",
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\s13.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 283749  =      0.000 ...  1134.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "45 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 45 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n",
      "Extracting EDF parameters from D:\\complete_yt\\EEG_classification\\dataverse_files\\s14.edf...\n",
      "EDF file detected\n",
      "Setting channel info structure...\n",
      "Creating raw.info structure...\n",
      "Reading 0 ... 542499  =      0.000 ...  2169.996 secs...\n",
      "EEG channel type selected for re-referencing\n",
      "Applying average reference.\n",
      "Applying a custom EEG reference.\n",
      "Filtering raw data in 1 contiguous segment\n",
      "Setting up band-pass filter from 1 - 45 Hz\n",
      "\n",
      "FIR filter parameters\n",
      "---------------------\n",
      "Designing a one-pass, zero-phase, non-causal bandpass filter:\n",
      "- Windowed time-domain design (firwin) method\n",
      "- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation\n",
      "- Lower passband edge: 1.00\n",
      "- Lower transition bandwidth: 1.00 Hz (-6 dB cutoff frequency: 0.50 Hz)\n",
      "- Upper passband edge: 45.00 Hz\n",
      "- Upper transition bandwidth: 11.25 Hz (-6 dB cutoff frequency: 50.62 Hz)\n",
      "- Filter length: 825 samples (3.300 sec)\n",
      "\n",
      "Not setting metadata\n",
      "Not setting metadata\n",
      "86 matching events found\n",
      "No baseline correction applied\n",
      "0 projection items activated\n",
      "Loading data for 86 events and 6250 original time points ...\n",
      "0 bad epochs dropped\n"
     ]
    }
   ],
   "source": [
    "control_epochs_array=[read_data(subject) for subject in healthy_file_path]\n",
    "patients_epochs_array=[read_data(subject) for subject in patient_file_path]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "1110efbc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "14 14\n"
     ]
    }
   ],
   "source": [
    "control_epochs_labels=[len(i)*[0] for i in control_epochs_array]\n",
    "patients_epochs_labels=[len(i)*[1] for i in patients_epochs_array]\n",
    "print(len(control_epochs_labels),len(patients_epochs_labels))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f4993102",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "28 28\n"
     ]
    }
   ],
   "source": [
    "data_list=control_epochs_array+patients_epochs_array\n",
    "label_list=control_epochs_labels+patients_epochs_labels\n",
    "print(len(data_list),len(label_list))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "4ea68f45",
   "metadata": {},
   "outputs": [],
   "source": [
    "groups_list=[[i]*len(j) for i, j in enumerate(data_list)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "b6f64fbb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1142, 6250, 19) (1142,) (1142,)\n"
     ]
    }
   ],
   "source": [
    "data_array=np.vstack(data_list)\n",
    "label_array=np.hstack(label_list)\n",
    "group_array=np.hstack(groups_list)\n",
    "data_array=np.moveaxis(data_array,1,2)\n",
    "\n",
    "print(data_array.shape,label_array.shape,group_array.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "43d462a7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "conv1d (Conv1D)              (None, 6248, 5)           290       \n",
      "_________________________________________________________________\n",
      "batch_normalization (BatchNo (None, 6248, 5)           20        \n",
      "_________________________________________________________________\n",
      "leaky_re_lu (LeakyReLU)      (None, 6248, 5)           0         \n",
      "_________________________________________________________________\n",
      "max_pooling1d (MaxPooling1D) (None, 3124, 5)           0         \n",
      "_________________________________________________________________\n",
      "conv1d_1 (Conv1D)            (None, 3122, 5)           80        \n",
      "_________________________________________________________________\n",
      "leaky_re_lu_1 (LeakyReLU)    (None, 3122, 5)           0         \n",
      "_________________________________________________________________\n",
      "max_pooling1d_1 (MaxPooling1 (None, 1561, 5)           0         \n",
      "_________________________________________________________________\n",
      "dropout (Dropout)            (None, 1561, 5)           0         \n",
      "_________________________________________________________________\n",
      "conv1d_2 (Conv1D)            (None, 1559, 5)           80        \n",
      "_________________________________________________________________\n",
      "leaky_re_lu_2 (LeakyReLU)    (None, 1559, 5)           0         \n",
      "_________________________________________________________________\n",
      "average_pooling1d (AveragePo (None, 779, 5)            0         \n",
      "_________________________________________________________________\n",
      "dropout_1 (Dropout)          (None, 779, 5)            0         \n",
      "_________________________________________________________________\n",
      "conv1d_3 (Conv1D)            (None, 777, 5)            80        \n",
      "_________________________________________________________________\n",
      "leaky_re_lu_3 (LeakyReLU)    (None, 777, 5)            0         \n",
      "_________________________________________________________________\n",
      "average_pooling1d_1 (Average (None, 388, 5)            0         \n",
      "_________________________________________________________________\n",
      "conv1d_4 (Conv1D)            (None, 386, 5)            80        \n",
      "_________________________________________________________________\n",
      "leaky_re_lu_4 (LeakyReLU)    (None, 386, 5)            0         \n",
      "_________________________________________________________________\n",
      "global_average_pooling1d (Gl (None, 5)                 0         \n",
      "_________________________________________________________________\n",
      "dense (Dense)                (None, 1)                 6         \n",
      "=================================================================\n",
      "Total params: 636\n",
      "Trainable params: 626\n",
      "Non-trainable params: 10\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "from tensorflow.keras.layers import Conv1D,BatchNormalization,LeakyReLU,MaxPool1D,\\\n",
    "GlobalAveragePooling1D,Dense,Dropout,AveragePooling1D\n",
    "from tensorflow.keras.models import Sequential\n",
    "from tensorflow.keras.backend import clear_session\n",
    "def cnnmodel():\n",
    "    clear_session()\n",
    "    model=Sequential()\n",
    "    model.add(Conv1D(filters=5,kernel_size=3,strides=1,input_shape=(6250,19)))#1\n",
    "    model.add(BatchNormalization())\n",
    "    model.add(LeakyReLU())\n",
    "    model.add(MaxPool1D(pool_size=2,strides=2))#2\n",
    "    model.add(Conv1D(filters=5,kernel_size=3,strides=1))#3\n",
    "    model.add(LeakyReLU())\n",
    "    model.add(MaxPool1D(pool_size=2,strides=2))#4\n",
    "    model.add(Dropout(0.5))\n",
    "    model.add(Conv1D(filters=5,kernel_size=3,strides=1))#5\n",
    "    model.add(LeakyReLU())\n",
    "    model.add(AveragePooling1D(pool_size=2,strides=2))#6\n",
    "    model.add(Dropout(0.5))\n",
    "    model.add(Conv1D(filters=5,kernel_size=3,strides=1))#7\n",
    "    model.add(LeakyReLU())\n",
    "    model.add(AveragePooling1D(pool_size=2,strides=2))#8\n",
    "    model.add(Conv1D(filters=5,kernel_size=3,strides=1))#9\n",
    "    model.add(LeakyReLU())\n",
    "    model.add(GlobalAveragePooling1D())#10\n",
    "    model.add(Dense(1,activation='sigmoid'))#11\n",
    "    \n",
    "    model.compile('adam',loss='binary_crossentropy',metrics=['accuracy'])\n",
    "    return model\n",
    "\n",
    "model=cnnmodel()\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "67b7474d",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import GroupKFold,LeaveOneGroupOut\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "gkf=GroupKFold()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "9f03d9a5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/50\n",
      "8/8 [==============================] - 1s 50ms/step - loss: 0.6880 - accuracy: 0.5231 - val_loss: 0.6775 - val_accuracy: 0.6450\n",
      "Epoch 2/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.6881 - accuracy: 0.5070 - val_loss: 0.6855 - val_accuracy: 0.5281\n",
      "Epoch 3/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6851 - accuracy: 0.5161 - val_loss: 0.6757 - val_accuracy: 0.7446\n",
      "Epoch 4/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6810 - accuracy: 0.5257 - val_loss: 0.6673 - val_accuracy: 0.7013\n",
      "Epoch 5/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6804 - accuracy: 0.5100 - val_loss: 0.6663 - val_accuracy: 0.7316\n",
      "Epoch 6/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6767 - accuracy: 0.5362 - val_loss: 0.6721 - val_accuracy: 0.6840\n",
      "Epoch 7/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6732 - accuracy: 0.5649 - val_loss: 0.6801 - val_accuracy: 0.5281\n",
      "Epoch 8/50\n",
      "8/8 [==============================] - 0s 33ms/step - loss: 0.6750 - accuracy: 0.6127 - val_loss: 0.6818 - val_accuracy: 0.4892\n",
      "Epoch 9/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6702 - accuracy: 0.6293 - val_loss: 0.6752 - val_accuracy: 0.5325\n",
      "Epoch 10/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.6635 - accuracy: 0.5749 - val_loss: 0.6648 - val_accuracy: 0.6277\n",
      "Epoch 11/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6569 - accuracy: 0.5893 - val_loss: 0.6553 - val_accuracy: 0.7229\n",
      "Epoch 12/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6569 - accuracy: 0.5671 - val_loss: 0.6705 - val_accuracy: 0.4935\n",
      "Epoch 13/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6535 - accuracy: 0.6353 - val_loss: 0.6611 - val_accuracy: 0.5281\n",
      "Epoch 14/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6389 - accuracy: 0.6312 - val_loss: 0.6604 - val_accuracy: 0.5152\n",
      "Epoch 15/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.6335 - accuracy: 0.7081 - val_loss: 0.6478 - val_accuracy: 0.6277\n",
      "Epoch 16/50\n",
      "8/8 [==============================] - 0s 33ms/step - loss: 0.6159 - accuracy: 0.7032 - val_loss: 0.6367 - val_accuracy: 0.6450\n",
      "Epoch 17/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.6244 - accuracy: 0.6469 - val_loss: 0.6644 - val_accuracy: 0.5411\n",
      "Epoch 18/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.5996 - accuracy: 0.7147 - val_loss: 0.6458 - val_accuracy: 0.6147\n",
      "Epoch 19/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.5932 - accuracy: 0.7396 - val_loss: 0.6029 - val_accuracy: 0.7273\n",
      "Epoch 20/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.6063 - accuracy: 0.7044 - val_loss: 0.6788 - val_accuracy: 0.5325\n",
      "Epoch 21/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.5802 - accuracy: 0.7032 - val_loss: 0.6364 - val_accuracy: 0.6234\n",
      "Epoch 22/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.5580 - accuracy: 0.7800 - val_loss: 0.5969 - val_accuracy: 0.7143\n",
      "Epoch 23/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.5391 - accuracy: 0.7675 - val_loss: 0.5997 - val_accuracy: 0.6623\n",
      "Epoch 24/50\n",
      "8/8 [==============================] - 0s 33ms/step - loss: 0.5329 - accuracy: 0.7654 - val_loss: 0.5999 - val_accuracy: 0.6407\n",
      "Epoch 25/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.5392 - accuracy: 0.7448 - val_loss: 0.6685 - val_accuracy: 0.5455\n",
      "Epoch 26/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.5185 - accuracy: 0.7506 - val_loss: 0.5918 - val_accuracy: 0.6623\n",
      "Epoch 27/50\n",
      "8/8 [==============================] - 0s 33ms/step - loss: 0.4812 - accuracy: 0.7884 - val_loss: 0.5397 - val_accuracy: 0.7792\n",
      "Epoch 28/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.4694 - accuracy: 0.8144 - val_loss: 0.6283 - val_accuracy: 0.5801\n",
      "Epoch 29/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.4621 - accuracy: 0.7945 - val_loss: 0.5710 - val_accuracy: 0.7056\n",
      "Epoch 30/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.4273 - accuracy: 0.8303 - val_loss: 0.5412 - val_accuracy: 0.7749\n",
      "Epoch 31/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.4302 - accuracy: 0.8356 - val_loss: 0.5370 - val_accuracy: 0.7706\n",
      "Epoch 32/50\n",
      "8/8 [==============================] - 0s 33ms/step - loss: 0.4021 - accuracy: 0.8505 - val_loss: 0.5606 - val_accuracy: 0.7532\n",
      "Epoch 33/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.3804 - accuracy: 0.8536 - val_loss: 0.5051 - val_accuracy: 0.8139\n",
      "Epoch 34/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.3587 - accuracy: 0.8727 - val_loss: 0.6488 - val_accuracy: 0.6580\n",
      "Epoch 35/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.3904 - accuracy: 0.8283 - val_loss: 0.5178 - val_accuracy: 0.8052\n",
      "Epoch 36/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.3406 - accuracy: 0.8789 - val_loss: 0.5222 - val_accuracy: 0.8009\n",
      "Epoch 37/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.3411 - accuracy: 0.8847 - val_loss: 0.5710 - val_accuracy: 0.7792\n",
      "Epoch 38/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.3272 - accuracy: 0.8845 - val_loss: 0.5855 - val_accuracy: 0.7706\n",
      "Epoch 39/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.2934 - accuracy: 0.8985 - val_loss: 0.5951 - val_accuracy: 0.7619\n",
      "Epoch 40/50\n",
      "8/8 [==============================] - 0s 33ms/step - loss: 0.2945 - accuracy: 0.8998 - val_loss: 0.5899 - val_accuracy: 0.7662\n",
      "Epoch 41/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.2892 - accuracy: 0.8678 - val_loss: 0.6510 - val_accuracy: 0.7532\n",
      "Epoch 42/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.3248 - accuracy: 0.8758 - val_loss: 0.6281 - val_accuracy: 0.7619\n",
      "Epoch 43/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.3193 - accuracy: 0.8479 - val_loss: 0.6972 - val_accuracy: 0.7273\n",
      "Epoch 44/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.2349 - accuracy: 0.9345 - val_loss: 0.7197 - val_accuracy: 0.7316\n",
      "Epoch 45/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.2739 - accuracy: 0.9102 - val_loss: 0.7474 - val_accuracy: 0.7143\n",
      "Epoch 46/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.2256 - accuracy: 0.9214 - val_loss: 0.7896 - val_accuracy: 0.7186\n",
      "Epoch 47/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.2224 - accuracy: 0.9390 - val_loss: 0.7569 - val_accuracy: 0.7446\n",
      "Epoch 48/50\n",
      "8/8 [==============================] - 0s 27ms/step - loss: 0.2558 - accuracy: 0.9103 - val_loss: 0.9568 - val_accuracy: 0.6797\n",
      "Epoch 49/50\n",
      "8/8 [==============================] - 0s 26ms/step - loss: 0.2308 - accuracy: 0.9361 - val_loss: 0.8982 - val_accuracy: 0.7273\n",
      "Epoch 50/50\n",
      "8/8 [==============================] - 0s 25ms/step - loss: 0.2379 - accuracy: 0.9146 - val_loss: 0.7763 - val_accuracy: 0.7446\n",
      "8/8 [==============================] - 0s 5ms/step - loss: 0.7763 - accuracy: 0.7446\n",
      "Epoch 1/50\n",
      "8/8 [==============================] - 1s 49ms/step - loss: 0.6992 - accuracy: 0.4292 - val_loss: 0.6929 - val_accuracy: 0.4660\n",
      "Epoch 2/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6928 - accuracy: 0.5354 - val_loss: 0.6930 - val_accuracy: 0.4709\n",
      "Epoch 3/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6884 - accuracy: 0.5764 - val_loss: 0.6934 - val_accuracy: 0.4709\n",
      "Epoch 4/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6855 - accuracy: 0.5619 - val_loss: 0.6942 - val_accuracy: 0.4709\n",
      "Epoch 5/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6803 - accuracy: 0.5642 - val_loss: 0.6965 - val_accuracy: 0.4709\n",
      "Epoch 6/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.6746 - accuracy: 0.5687 - val_loss: 0.7015 - val_accuracy: 0.4709\n",
      "Epoch 7/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.6767 - accuracy: 0.5485 - val_loss: 0.7070 - val_accuracy: 0.4709\n",
      "Epoch 8/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6655 - accuracy: 0.5900 - val_loss: 0.7125 - val_accuracy: 0.4709\n",
      "Epoch 9/50\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8/8 [==============================] - 0s 32ms/step - loss: 0.6687 - accuracy: 0.5552 - val_loss: 0.7081 - val_accuracy: 0.4709\n",
      "Epoch 10/50\n",
      "8/8 [==============================] - 0s 33ms/step - loss: 0.6618 - accuracy: 0.5555 - val_loss: 0.7053 - val_accuracy: 0.4709\n",
      "Epoch 11/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.6548 - accuracy: 0.5740 - val_loss: 0.7065 - val_accuracy: 0.4709\n",
      "Epoch 12/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.6592 - accuracy: 0.5579 - val_loss: 0.7027 - val_accuracy: 0.4709\n",
      "Epoch 13/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.6402 - accuracy: 0.5689 - val_loss: 0.7024 - val_accuracy: 0.4709\n",
      "Epoch 14/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.6413 - accuracy: 0.5592 - val_loss: 0.7012 - val_accuracy: 0.4709\n",
      "Epoch 15/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6260 - accuracy: 0.5738 - val_loss: 0.6956 - val_accuracy: 0.4709\n",
      "Epoch 16/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6306 - accuracy: 0.5638 - val_loss: 0.6911 - val_accuracy: 0.4709\n",
      "Epoch 17/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.6257 - accuracy: 0.6014 - val_loss: 0.6895 - val_accuracy: 0.4709\n",
      "Epoch 18/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.6126 - accuracy: 0.5906 - val_loss: 0.6801 - val_accuracy: 0.4806\n",
      "Epoch 19/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.6003 - accuracy: 0.5884 - val_loss: 0.6725 - val_accuracy: 0.4757\n",
      "Epoch 20/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.5904 - accuracy: 0.7025 - val_loss: 0.6705 - val_accuracy: 0.4660\n",
      "Epoch 21/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.5778 - accuracy: 0.7080 - val_loss: 0.6560 - val_accuracy: 0.5534\n",
      "Epoch 22/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.5347 - accuracy: 0.7456 - val_loss: 0.6479 - val_accuracy: 0.6214\n",
      "Epoch 23/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.5256 - accuracy: 0.7519 - val_loss: 0.6593 - val_accuracy: 0.5728\n",
      "Epoch 24/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.5409 - accuracy: 0.7223 - val_loss: 0.6579 - val_accuracy: 0.5728\n",
      "Epoch 25/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.4598 - accuracy: 0.8133 - val_loss: 0.6578 - val_accuracy: 0.5971\n",
      "Epoch 26/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.4749 - accuracy: 0.7643 - val_loss: 0.6828 - val_accuracy: 0.5534\n",
      "Epoch 27/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.4609 - accuracy: 0.7845 - val_loss: 0.7158 - val_accuracy: 0.5194\n",
      "Epoch 28/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.4638 - accuracy: 0.7709 - val_loss: 0.6721 - val_accuracy: 0.5922\n",
      "Epoch 29/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.4097 - accuracy: 0.8069 - val_loss: 0.6755 - val_accuracy: 0.6068\n",
      "Epoch 30/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.4248 - accuracy: 0.7967 - val_loss: 0.7232 - val_accuracy: 0.5340\n",
      "Epoch 31/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.3992 - accuracy: 0.8022 - val_loss: 0.7114 - val_accuracy: 0.5388\n",
      "Epoch 32/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.4047 - accuracy: 0.8096 - val_loss: 0.7352 - val_accuracy: 0.5340\n",
      "Epoch 33/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.3807 - accuracy: 0.8282 - val_loss: 0.7200 - val_accuracy: 0.5534\n",
      "Epoch 34/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.3959 - accuracy: 0.8042 - val_loss: 0.7758 - val_accuracy: 0.5243\n",
      "Epoch 35/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.3923 - accuracy: 0.8218 - val_loss: 0.7524 - val_accuracy: 0.5291\n",
      "Epoch 36/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.4196 - accuracy: 0.7611 - val_loss: 0.7426 - val_accuracy: 0.5437\n",
      "Epoch 37/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.3430 - accuracy: 0.8337 - val_loss: 0.7573 - val_accuracy: 0.5437\n",
      "Epoch 38/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.3494 - accuracy: 0.8386 - val_loss: 0.8896 - val_accuracy: 0.5000\n",
      "Epoch 39/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.3383 - accuracy: 0.8454 - val_loss: 0.8402 - val_accuracy: 0.5291\n",
      "Epoch 40/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.3163 - accuracy: 0.8622 - val_loss: 0.8257 - val_accuracy: 0.5291\n",
      "Epoch 41/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.3455 - accuracy: 0.8418 - val_loss: 0.8891 - val_accuracy: 0.5146\n",
      "Epoch 42/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.3325 - accuracy: 0.8493 - val_loss: 0.8781 - val_accuracy: 0.5291\n",
      "Epoch 43/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.3347 - accuracy: 0.8522 - val_loss: 0.9190 - val_accuracy: 0.5243\n",
      "Epoch 44/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.2908 - accuracy: 0.8790 - val_loss: 1.0160 - val_accuracy: 0.5146\n",
      "Epoch 45/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.3166 - accuracy: 0.8570 - val_loss: 1.0992 - val_accuracy: 0.5049\n",
      "Epoch 46/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.2885 - accuracy: 0.8711 - val_loss: 0.9946 - val_accuracy: 0.5146\n",
      "Epoch 47/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.2942 - accuracy: 0.8641 - val_loss: 0.9882 - val_accuracy: 0.5243\n",
      "Epoch 48/50\n",
      "8/8 [==============================] - 0s 24ms/step - loss: 0.2560 - accuracy: 0.9022 - val_loss: 1.1211 - val_accuracy: 0.5291\n",
      "Epoch 49/50\n",
      "8/8 [==============================] - 0s 25ms/step - loss: 0.2621 - accuracy: 0.8919 - val_loss: 1.1908 - val_accuracy: 0.5194\n",
      "Epoch 50/50\n",
      "8/8 [==============================] - 0s 24ms/step - loss: 0.2723 - accuracy: 0.8807 - val_loss: 1.2554 - val_accuracy: 0.5049\n",
      "7/7 [==============================] - 0s 5ms/step - loss: 1.2554 - accuracy: 0.5049\n",
      "Epoch 1/50\n",
      "8/8 [==============================] - 1s 49ms/step - loss: 0.6976 - accuracy: 0.4363 - val_loss: 0.6928 - val_accuracy: 0.4915\n",
      "Epoch 2/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6940 - accuracy: 0.4860 - val_loss: 0.6922 - val_accuracy: 0.5000\n",
      "Epoch 3/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.6925 - accuracy: 0.5384 - val_loss: 0.6919 - val_accuracy: 0.5000\n",
      "Epoch 4/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6906 - accuracy: 0.5549 - val_loss: 0.6919 - val_accuracy: 0.5000\n",
      "Epoch 5/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6880 - accuracy: 0.5583 - val_loss: 0.6926 - val_accuracy: 0.5000\n",
      "Epoch 6/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6862 - accuracy: 0.5485 - val_loss: 0.6940 - val_accuracy: 0.5000\n",
      "Epoch 7/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6803 - accuracy: 0.5639 - val_loss: 0.6967 - val_accuracy: 0.5000\n",
      "Epoch 8/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.6823 - accuracy: 0.5464 - val_loss: 0.6980 - val_accuracy: 0.5000\n",
      "Epoch 9/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6728 - accuracy: 0.5655 - val_loss: 0.6964 - val_accuracy: 0.5000\n",
      "Epoch 10/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6667 - accuracy: 0.5762 - val_loss: 0.6968 - val_accuracy: 0.5000\n",
      "Epoch 11/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6647 - accuracy: 0.5691 - val_loss: 0.6973 - val_accuracy: 0.5000\n",
      "Epoch 12/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6559 - accuracy: 0.5802 - val_loss: 0.6967 - val_accuracy: 0.5000\n",
      "Epoch 13/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.6573 - accuracy: 0.5550 - val_loss: 0.6925 - val_accuracy: 0.5000\n",
      "Epoch 14/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6433 - accuracy: 0.5734 - val_loss: 0.6898 - val_accuracy: 0.5000\n",
      "Epoch 15/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.6332 - accuracy: 0.5749 - val_loss: 0.6804 - val_accuracy: 0.5000\n",
      "Epoch 16/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6332 - accuracy: 0.5570 - val_loss: 0.6696 - val_accuracy: 0.5000\n",
      "Epoch 17/50\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "8/8 [==============================] - 0s 30ms/step - loss: 0.6213 - accuracy: 0.5871 - val_loss: 0.6631 - val_accuracy: 0.5000\n",
      "Epoch 18/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6037 - accuracy: 0.5872 - val_loss: 0.6564 - val_accuracy: 0.5000\n",
      "Epoch 19/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.5757 - accuracy: 0.6572 - val_loss: 0.6507 - val_accuracy: 0.5000\n",
      "Epoch 20/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.5552 - accuracy: 0.7181 - val_loss: 0.6249 - val_accuracy: 0.5427\n",
      "Epoch 21/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.5364 - accuracy: 0.8584 - val_loss: 0.6052 - val_accuracy: 0.6709\n",
      "Epoch 22/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.4916 - accuracy: 0.8721 - val_loss: 0.5976 - val_accuracy: 0.6667\n",
      "Epoch 23/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.4559 - accuracy: 0.8512 - val_loss: 0.5569 - val_accuracy: 0.7521\n",
      "Epoch 24/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.4299 - accuracy: 0.8701 - val_loss: 0.5258 - val_accuracy: 0.8162\n",
      "Epoch 25/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.3668 - accuracy: 0.9024 - val_loss: 0.5361 - val_accuracy: 0.7521\n",
      "Epoch 26/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.3070 - accuracy: 0.9123 - val_loss: 0.4776 - val_accuracy: 0.8504\n",
      "Epoch 27/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.2868 - accuracy: 0.9110 - val_loss: 0.5353 - val_accuracy: 0.7479\n",
      "Epoch 28/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.2538 - accuracy: 0.9255 - val_loss: 0.5034 - val_accuracy: 0.8034\n",
      "Epoch 29/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.2400 - accuracy: 0.9276 - val_loss: 0.5490 - val_accuracy: 0.7607\n",
      "Epoch 30/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.2308 - accuracy: 0.9217 - val_loss: 0.4621 - val_accuracy: 0.8632\n",
      "Epoch 31/50\n",
      "8/8 [==============================] - 0s 33ms/step - loss: 0.1816 - accuracy: 0.9471 - val_loss: 0.5187 - val_accuracy: 0.8120\n",
      "Epoch 32/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.1949 - accuracy: 0.9423 - val_loss: 0.5827 - val_accuracy: 0.7650\n",
      "Epoch 33/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.1699 - accuracy: 0.9410 - val_loss: 0.6067 - val_accuracy: 0.7607\n",
      "Epoch 34/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.1497 - accuracy: 0.9502 - val_loss: 0.5036 - val_accuracy: 0.8504\n",
      "Epoch 35/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.1704 - accuracy: 0.9449 - val_loss: 0.5092 - val_accuracy: 0.8462\n",
      "Epoch 36/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.1340 - accuracy: 0.9708 - val_loss: 0.6811 - val_accuracy: 0.7479\n",
      "Epoch 37/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.1395 - accuracy: 0.9498 - val_loss: 0.5976 - val_accuracy: 0.8077\n",
      "Epoch 38/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.1295 - accuracy: 0.9786 - val_loss: 0.5037 - val_accuracy: 0.8590\n",
      "Epoch 39/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.1331 - accuracy: 0.9600 - val_loss: 0.7318 - val_accuracy: 0.7479\n",
      "Epoch 40/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.1371 - accuracy: 0.9601 - val_loss: 0.5689 - val_accuracy: 0.8162\n",
      "Epoch 41/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.1017 - accuracy: 0.9706 - val_loss: 0.6287 - val_accuracy: 0.7863\n",
      "Epoch 42/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.1044 - accuracy: 0.9760 - val_loss: 0.6943 - val_accuracy: 0.7778\n",
      "Epoch 43/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.1256 - accuracy: 0.9593 - val_loss: 0.7219 - val_accuracy: 0.7735\n",
      "Epoch 44/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.1041 - accuracy: 0.9745 - val_loss: 0.7434 - val_accuracy: 0.7735\n",
      "Epoch 45/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.1112 - accuracy: 0.9588 - val_loss: 0.9246 - val_accuracy: 0.7350\n",
      "Epoch 46/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.1189 - accuracy: 0.9656 - val_loss: 0.6627 - val_accuracy: 0.8077\n",
      "Epoch 47/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.1054 - accuracy: 0.9613 - val_loss: 0.7323 - val_accuracy: 0.7735\n",
      "Epoch 48/50\n",
      "8/8 [==============================] - 0s 24ms/step - loss: 0.0923 - accuracy: 0.9739 - val_loss: 0.8662 - val_accuracy: 0.7350\n",
      "Epoch 49/50\n",
      "8/8 [==============================] - 0s 24ms/step - loss: 0.1013 - accuracy: 0.9732 - val_loss: 0.8553 - val_accuracy: 0.7350\n",
      "Epoch 50/50\n",
      "8/8 [==============================] - 0s 24ms/step - loss: 0.0801 - accuracy: 0.9794 - val_loss: 0.6903 - val_accuracy: 0.7949\n",
      "8/8 [==============================] - 0s 5ms/step - loss: 0.6903 - accuracy: 0.7949\n",
      "Epoch 1/50\n",
      "8/8 [==============================] - 1s 49ms/step - loss: 0.7341 - accuracy: 0.4397 - val_loss: 0.6931 - val_accuracy: 0.4534\n",
      "Epoch 2/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.7069 - accuracy: 0.4538 - val_loss: 0.6906 - val_accuracy: 0.6059\n",
      "Epoch 3/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.6995 - accuracy: 0.4397 - val_loss: 0.6896 - val_accuracy: 0.5466\n",
      "Epoch 4/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.6920 - accuracy: 0.5413 - val_loss: 0.6894 - val_accuracy: 0.5466\n",
      "Epoch 5/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.6889 - accuracy: 0.5425 - val_loss: 0.6893 - val_accuracy: 0.5466\n",
      "Epoch 6/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.6866 - accuracy: 0.5439 - val_loss: 0.6894 - val_accuracy: 0.5466\n",
      "Epoch 7/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6814 - accuracy: 0.5539 - val_loss: 0.6894 - val_accuracy: 0.5466\n",
      "Epoch 8/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6773 - accuracy: 0.5565 - val_loss: 0.6894 - val_accuracy: 0.5466\n",
      "Epoch 9/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.6771 - accuracy: 0.5433 - val_loss: 0.6897 - val_accuracy: 0.5466\n",
      "Epoch 10/50\n",
      "8/8 [==============================] - 0s 33ms/step - loss: 0.6717 - accuracy: 0.5533 - val_loss: 0.6902 - val_accuracy: 0.5466\n",
      "Epoch 11/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.6720 - accuracy: 0.5395 - val_loss: 0.6904 - val_accuracy: 0.5466\n",
      "Epoch 12/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.6701 - accuracy: 0.5464 - val_loss: 0.6911 - val_accuracy: 0.5466\n",
      "Epoch 13/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.6655 - accuracy: 0.5426 - val_loss: 0.6926 - val_accuracy: 0.5466\n",
      "Epoch 14/50\n",
      "8/8 [==============================] - 0s 33ms/step - loss: 0.6482 - accuracy: 0.5636 - val_loss: 0.6948 - val_accuracy: 0.5466\n",
      "Epoch 15/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.6574 - accuracy: 0.5489 - val_loss: 0.6970 - val_accuracy: 0.5466\n",
      "Epoch 16/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6460 - accuracy: 0.5594 - val_loss: 0.6990 - val_accuracy: 0.5466\n",
      "Epoch 17/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.6417 - accuracy: 0.5663 - val_loss: 0.7008 - val_accuracy: 0.4831\n",
      "Epoch 18/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.6394 - accuracy: 0.5729 - val_loss: 0.7029 - val_accuracy: 0.4534\n",
      "Epoch 19/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6315 - accuracy: 0.5671 - val_loss: 0.7051 - val_accuracy: 0.4534\n",
      "Epoch 20/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6392 - accuracy: 0.5971 - val_loss: 0.7079 - val_accuracy: 0.4534\n",
      "Epoch 21/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6280 - accuracy: 0.5999 - val_loss: 0.7122 - val_accuracy: 0.4449\n",
      "Epoch 22/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6139 - accuracy: 0.6241 - val_loss: 0.7186 - val_accuracy: 0.4322\n",
      "Epoch 23/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.6120 - accuracy: 0.6254 - val_loss: 0.7256 - val_accuracy: 0.3983\n",
      "Epoch 24/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.5952 - accuracy: 0.6043 - val_loss: 0.7335 - val_accuracy: 0.3602\n",
      "Epoch 25/50\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "8/8 [==============================] - 0s 32ms/step - loss: 0.6150 - accuracy: 0.6368 - val_loss: 0.7415 - val_accuracy: 0.3347\n",
      "Epoch 26/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.5908 - accuracy: 0.6644 - val_loss: 0.7519 - val_accuracy: 0.3390\n",
      "Epoch 27/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.5839 - accuracy: 0.7164 - val_loss: 0.7653 - val_accuracy: 0.3390\n",
      "Epoch 28/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.5693 - accuracy: 0.7290 - val_loss: 0.7820 - val_accuracy: 0.3390\n",
      "Epoch 29/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.5771 - accuracy: 0.7224 - val_loss: 0.7945 - val_accuracy: 0.3347\n",
      "Epoch 30/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.5569 - accuracy: 0.7292 - val_loss: 0.8099 - val_accuracy: 0.3390\n",
      "Epoch 31/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.5660 - accuracy: 0.6951 - val_loss: 0.8239 - val_accuracy: 0.3347\n",
      "Epoch 32/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.5344 - accuracy: 0.7735 - val_loss: 0.8398 - val_accuracy: 0.3390\n",
      "Epoch 33/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.5590 - accuracy: 0.6864 - val_loss: 0.8517 - val_accuracy: 0.3347\n",
      "Epoch 34/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.5364 - accuracy: 0.7270 - val_loss: 0.8791 - val_accuracy: 0.3347\n",
      "Epoch 35/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.5392 - accuracy: 0.7307 - val_loss: 0.8832 - val_accuracy: 0.3305\n",
      "Epoch 36/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.5047 - accuracy: 0.7863 - val_loss: 0.8942 - val_accuracy: 0.3305\n",
      "Epoch 37/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.5200 - accuracy: 0.7475 - val_loss: 0.9070 - val_accuracy: 0.3305\n",
      "Epoch 38/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.5366 - accuracy: 0.7093 - val_loss: 0.9327 - val_accuracy: 0.3305\n",
      "Epoch 39/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.5057 - accuracy: 0.7584 - val_loss: 0.9496 - val_accuracy: 0.3305\n",
      "Epoch 40/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.5206 - accuracy: 0.7411 - val_loss: 0.9878 - val_accuracy: 0.3305\n",
      "Epoch 41/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.5188 - accuracy: 0.7550 - val_loss: 1.0252 - val_accuracy: 0.3347\n",
      "Epoch 42/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.4921 - accuracy: 0.7596 - val_loss: 1.0248 - val_accuracy: 0.3305\n",
      "Epoch 43/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.5199 - accuracy: 0.7470 - val_loss: 1.0517 - val_accuracy: 0.3347\n",
      "Epoch 44/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.4791 - accuracy: 0.7708 - val_loss: 1.0989 - val_accuracy: 0.3305\n",
      "Epoch 45/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.4707 - accuracy: 0.7753 - val_loss: 1.1212 - val_accuracy: 0.3305\n",
      "Epoch 46/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.4995 - accuracy: 0.7274 - val_loss: 1.1282 - val_accuracy: 0.3347\n",
      "Epoch 47/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.4864 - accuracy: 0.7400 - val_loss: 1.1350 - val_accuracy: 0.3347\n",
      "Epoch 48/50\n",
      "8/8 [==============================] - 0s 24ms/step - loss: 0.4651 - accuracy: 0.7493 - val_loss: 1.1383 - val_accuracy: 0.3432\n",
      "Epoch 49/50\n",
      "8/8 [==============================] - 0s 24ms/step - loss: 0.4878 - accuracy: 0.7575 - val_loss: 1.1336 - val_accuracy: 0.3644\n",
      "Epoch 50/50\n",
      "8/8 [==============================] - 0s 24ms/step - loss: 0.4529 - accuracy: 0.7793 - val_loss: 1.1441 - val_accuracy: 0.3771\n",
      "8/8 [==============================] - 0s 5ms/step - loss: 1.1441 - accuracy: 0.3771\n",
      "Epoch 1/50\n",
      "8/8 [==============================] - 1s 48ms/step - loss: 0.6964 - accuracy: 0.4556 - val_loss: 0.6925 - val_accuracy: 0.5319\n",
      "Epoch 2/50\n",
      "8/8 [==============================] - 0s 35ms/step - loss: 0.6880 - accuracy: 0.5466 - val_loss: 0.6878 - val_accuracy: 0.5319\n",
      "Epoch 3/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.6847 - accuracy: 0.5516 - val_loss: 0.6862 - val_accuracy: 0.5319\n",
      "Epoch 4/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6848 - accuracy: 0.5510 - val_loss: 0.6862 - val_accuracy: 0.5319\n",
      "Epoch 5/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.6793 - accuracy: 0.5606 - val_loss: 0.6854 - val_accuracy: 0.5319\n",
      "Epoch 6/50\n",
      "8/8 [==============================] - 0s 35ms/step - loss: 0.6775 - accuracy: 0.5618 - val_loss: 0.6841 - val_accuracy: 0.5319\n",
      "Epoch 7/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6835 - accuracy: 0.5358 - val_loss: 0.6828 - val_accuracy: 0.5319\n",
      "Epoch 8/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6770 - accuracy: 0.5461 - val_loss: 0.6808 - val_accuracy: 0.5319\n",
      "Epoch 9/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6749 - accuracy: 0.5468 - val_loss: 0.6795 - val_accuracy: 0.5319\n",
      "Epoch 10/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.6697 - accuracy: 0.5510 - val_loss: 0.6775 - val_accuracy: 0.5319\n",
      "Epoch 11/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.6668 - accuracy: 0.5573 - val_loss: 0.6739 - val_accuracy: 0.5319\n",
      "Epoch 12/50\n",
      "8/8 [==============================] - 0s 35ms/step - loss: 0.6648 - accuracy: 0.5516 - val_loss: 0.6705 - val_accuracy: 0.5319\n",
      "Epoch 13/50\n",
      "8/8 [==============================] - 0s 34ms/step - loss: 0.6574 - accuracy: 0.5495 - val_loss: 0.6685 - val_accuracy: 0.5319\n",
      "Epoch 14/50\n",
      "8/8 [==============================] - 0s 34ms/step - loss: 0.6593 - accuracy: 0.5370 - val_loss: 0.6678 - val_accuracy: 0.5319\n",
      "Epoch 15/50\n",
      "8/8 [==============================] - 0s 34ms/step - loss: 0.6557 - accuracy: 0.5366 - val_loss: 0.6677 - val_accuracy: 0.7660\n",
      "Epoch 16/50\n",
      "8/8 [==============================] - 0s 34ms/step - loss: 0.6373 - accuracy: 0.5877 - val_loss: 0.6638 - val_accuracy: 0.8936\n",
      "Epoch 17/50\n",
      "8/8 [==============================] - 0s 44ms/step - loss: 0.6280 - accuracy: 0.5900 - val_loss: 0.6531 - val_accuracy: 0.9021\n",
      "Epoch 18/50\n",
      "8/8 [==============================] - 0s 34ms/step - loss: 0.6379 - accuracy: 0.5890 - val_loss: 0.6432 - val_accuracy: 0.9021\n",
      "Epoch 19/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6279 - accuracy: 0.5779 - val_loss: 0.6389 - val_accuracy: 0.8766\n",
      "Epoch 20/50\n",
      "8/8 [==============================] - 0s 35ms/step - loss: 0.6202 - accuracy: 0.6084 - val_loss: 0.6440 - val_accuracy: 0.8043\n",
      "Epoch 21/50\n",
      "8/8 [==============================] - 0s 35ms/step - loss: 0.6135 - accuracy: 0.6386 - val_loss: 0.6486 - val_accuracy: 0.5830\n",
      "Epoch 22/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.6041 - accuracy: 0.6411 - val_loss: 0.6399 - val_accuracy: 0.5872\n",
      "Epoch 23/50\n",
      "8/8 [==============================] - 0s 34ms/step - loss: 0.6008 - accuracy: 0.6213 - val_loss: 0.6529 - val_accuracy: 0.5277\n",
      "Epoch 24/50\n",
      "8/8 [==============================] - 0s 35ms/step - loss: 0.6058 - accuracy: 0.6655 - val_loss: 0.6434 - val_accuracy: 0.5319\n",
      "Epoch 25/50\n",
      "8/8 [==============================] - 0s 37ms/step - loss: 0.5727 - accuracy: 0.7157 - val_loss: 0.6551 - val_accuracy: 0.4979\n",
      "Epoch 26/50\n",
      "8/8 [==============================] - 0s 36ms/step - loss: 0.5817 - accuracy: 0.6983 - val_loss: 0.6137 - val_accuracy: 0.5702\n",
      "Epoch 27/50\n",
      "8/8 [==============================] - 0s 35ms/step - loss: 0.5404 - accuracy: 0.7604 - val_loss: 0.5932 - val_accuracy: 0.6128\n",
      "Epoch 28/50\n",
      "8/8 [==============================] - 0s 36ms/step - loss: 0.5371 - accuracy: 0.7815 - val_loss: 0.5918 - val_accuracy: 0.5830\n",
      "Epoch 29/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.5364 - accuracy: 0.7169 - val_loss: 0.5648 - val_accuracy: 0.6596\n",
      "Epoch 30/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.5195 - accuracy: 0.7489 - val_loss: 0.5389 - val_accuracy: 0.7617\n",
      "Epoch 31/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.4970 - accuracy: 0.7903 - val_loss: 0.5530 - val_accuracy: 0.6340\n",
      "Epoch 32/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.5167 - accuracy: 0.7366 - val_loss: 0.5180 - val_accuracy: 0.7362\n",
      "Epoch 33/50\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8/8 [==============================] - 0s 31ms/step - loss: 0.4856 - accuracy: 0.7933 - val_loss: 0.4400 - val_accuracy: 0.9489\n",
      "Epoch 34/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.4417 - accuracy: 0.8218 - val_loss: 0.5029 - val_accuracy: 0.7021\n",
      "Epoch 35/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.4433 - accuracy: 0.7901 - val_loss: 0.4253 - val_accuracy: 0.8979\n",
      "Epoch 36/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.4310 - accuracy: 0.8254 - val_loss: 0.3583 - val_accuracy: 0.9872\n",
      "Epoch 37/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.4262 - accuracy: 0.8275 - val_loss: 0.3716 - val_accuracy: 0.9447\n",
      "Epoch 38/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.3780 - accuracy: 0.8371 - val_loss: 0.3438 - val_accuracy: 0.9660\n",
      "Epoch 39/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.3406 - accuracy: 0.8807 - val_loss: 0.3362 - val_accuracy: 0.9830\n",
      "Epoch 40/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.3498 - accuracy: 0.8734 - val_loss: 0.3105 - val_accuracy: 0.9915\n",
      "Epoch 41/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.3425 - accuracy: 0.8806 - val_loss: 0.2951 - val_accuracy: 0.9915\n",
      "Epoch 42/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.3071 - accuracy: 0.8944 - val_loss: 0.2580 - val_accuracy: 0.9872\n",
      "Epoch 43/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.3011 - accuracy: 0.9082 - val_loss: 0.2715 - val_accuracy: 0.9957\n",
      "Epoch 44/50\n",
      "8/8 [==============================] - 0s 32ms/step - loss: 0.3011 - accuracy: 0.8908 - val_loss: 0.2259 - val_accuracy: 0.9915\n",
      "Epoch 45/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.2878 - accuracy: 0.8902 - val_loss: 0.2585 - val_accuracy: 0.9787\n",
      "Epoch 46/50\n",
      "8/8 [==============================] - 0s 30ms/step - loss: 0.3144 - accuracy: 0.8817 - val_loss: 0.2413 - val_accuracy: 0.9872\n",
      "Epoch 47/50\n",
      "8/8 [==============================] - 0s 31ms/step - loss: 0.2948 - accuracy: 0.9061 - val_loss: 0.2247 - val_accuracy: 0.9915\n",
      "Epoch 48/50\n",
      "8/8 [==============================] - 0s 26ms/step - loss: 0.2870 - accuracy: 0.9191 - val_loss: 0.2280 - val_accuracy: 0.9915\n",
      "Epoch 49/50\n",
      "8/8 [==============================] - 0s 24ms/step - loss: 0.2653 - accuracy: 0.9214 - val_loss: 0.2310 - val_accuracy: 0.9872\n",
      "Epoch 50/50\n",
      "8/8 [==============================] - 0s 24ms/step - loss: 0.2575 - accuracy: 0.9123 - val_loss: 0.2218 - val_accuracy: 0.9957\n",
      "8/8 [==============================] - 0s 5ms/step - loss: 0.2218 - accuracy: 0.9957\n"
     ]
    }
   ],
   "source": [
    "accuracy=[]\n",
    "for train_index, val_index in gkf.split(data_array, label_array, groups=group_array):\n",
    "    train_features,train_labels=data_array[train_index],label_array[train_index]\n",
    "    val_features,val_labels=data_array[val_index],label_array[val_index]\n",
    "    scaler=StandardScaler()\n",
    "    train_features = scaler.fit_transform(train_features.reshape(-1, train_features.shape[-1])).reshape(train_features.shape)\n",
    "    val_features = scaler.transform(val_features.reshape(-1, val_features.shape[-1])).reshape(val_features.shape)\n",
    "    model=cnnmodel()\n",
    "    model.fit(train_features,train_labels,epochs=50,batch_size=128,validation_data=(val_features,val_labels))\n",
    "    accuracy.append(model.evaluate(val_features,val_labels)[1])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "9c43d34e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6834356546401977"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean(accuracy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7b234956",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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