Run per-epoch training to check test-loss VS train-loss

MLP_train_vs_test_error.py

@@ -1,5 +1,6 @@
 import os
-from keras.models import model_from_json, Sequential
+from keras import optimizers
+from keras.models import model_from_json, Sequential, load_model
 from keras.layers import Activation, Dense, Dropout
 from keras.engine import Input, Model
 import keras.utils
@@ -23,7 +24,7 @@ def get_model(num_hid_layers, cells_per_layer, dropout_rate):
 	for i in range(num_hid_layers):
 		model.add(Dense(cells_per_layer, activation='relu'))
 		model.add(Dropout(dropout_rate))
-	model.add(Dense(1, activation='sigmoid'))#softmax se multiclass, sigmoid se 2class
+	model.add(Dense(5, activation='softmax'))#softmax se multiclass, sigmoid se 2class
 	model_name = models_directory + 'MLP.hidlay' + str(num_hid_layers) + '.cells' + str(cells_per_layer) + '.drop' + str(dropout_rate)
 	plot_model(model, to_file = model_name + '.2class' +  '.png', show_shapes=True)
 	fp_model = open(model_name + '.2class' + '.json', 'w+')
@@ -41,29 +42,29 @@ def fit_and_eval(dataset_id, num_hid_layers, cells_per_layer, dropout_rate):
 	#y_train = y_train[0:100]
 	#x_test = x_test[0:100,:]
 	#y_test = y_test[0:100]
-	num_classes = 2
-	nb_epoch = 500
-	optimizer = 'sgd'
-	loss_function = 'mse'
+	model_name = str(num_hid_layers) + '.' + str(cells_per_layer) + '.' + str(dropout_rate)
+	num_classes = 5
+	nb_epoch = 100
+	optimizer = 'rmsprop'
+	optimizer_w_params = optimizers.RMSprop(lr=0.0001)
+	loss_function = 'categorical_crossentropy'
 	results_file = 	results_directory + dataset_name + '.' + loss_function + '.' + optimizer + '.Dropout' + str(dropout_rate) + 'Layers' + str(num_hid_layers) + '.Cells' + str(cells_per_layer)
 	write_results(results_file, 'loss|acc|val_loss|val_acc')
 	model = get_model(num_hid_layers, cells_per_layer, dropout_rate)
 	model.compile(optimizer=optimizer, loss=loss_function, metrics=['accuracy'])
-	#model.fit(x_train, keras.utils.np_utils.to_categorical(y_train, num_classes), epochs = nb_epoch, batch_size = 128, shuffle=True)
-	hist = model.fit(x_train, y_train, validation_data=(x_test,y_test), epochs = nb_epoch, batch_size = 128, shuffle=True)
-	#ev = model.evaluate(x = x_test, y = keras.utils.np_utils.to_categorical(y_test, num_classes), batch_size = 128)
-	#ev = model.evaluate(x = x_test, y = y_test, batch_size = 128)
+	hist = model.fit(x_train, keras.utils.np_utils.to_categorical(y_train, num_classes), validation_data =(x_test,keras.utils.np_utils.to_categorical(y_test)), epochs = nb_epoch, batch_size = 128, shuffle=True)
+	#hist = model.fit(x_train, y_train, validation_data=(x_test,y_test), epochs = nb_epoch, batch_size = 128, shuffle=True)
 	write_results(results_file,hist.history['loss'])
 	write_results(results_file,hist.history['acc'])
 	write_results(results_file,hist.history['val_loss'])
 	write_results(results_file,hist.history['val_acc'])
+	model.save(models_directory + '/full_models/' + dataset_name + '.' + model_name + '.h5')
 
 def write_results(results_file, text):
 	fp_results = open(results_file, 'a')
 	fp_results.write(str(text))
 	fp_results.write('\n')
 	fp_results.close()
 
-fit_and_eval(3,1,40,0.5)
-fit_and_eval(3,4,40,0.5)
+fit_and_eval(0,2,30,0.4)
 

MLPmodels/MLP.hidlay1.cells40.drop0.5.2class.json

@@ -1 +1 @@
-{"config": [{"config": {"activation": "relu", "use_bias": true, "kernel_regularizer": null, "kernel_constraint": null, "name": "dense_1", "dtype": "float32", "batch_input_shape": [null, 79], "kernel_initializer": {"config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}, "class_name": "VarianceScaling"}, "bias_initializer": {"config": {}, "class_name": "Zeros"}, "trainable": true, "activity_regularizer": null, "bias_constraint": null, "bias_regularizer": null, "units": 40}, "class_name": "Dense"}, {"config": {"name": "dropout_1", "trainable": true, "rate": 0.5}, "class_name": "Dropout"}, {"config": {"activation": "relu", "use_bias": true, "kernel_constraint": null, "name": "dense_2", "bias_constraint": null, "kernel_initializer": {"config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}, "class_name": "VarianceScaling"}, "bias_initializer": {"config": {}, "class_name": "Zeros"}, "bias_regularizer": null, "trainable": true, "activity_regularizer": null, "kernel_regularizer": null, "units": 40}, "class_name": "Dense"}, {"config": {"name": "dropout_2", "trainable": true, "rate": 0.5}, "class_name": "Dropout"}, {"config": {"activation": "sigmoid", "use_bias": true, "kernel_constraint": null, "name": "dense_3", "bias_constraint": null, "kernel_initializer": {"config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}, "class_name": "VarianceScaling"}, "bias_initializer": {"config": {}, "class_name": "Zeros"}, "bias_regularizer": null, "trainable": true, "activity_regularizer": null, "kernel_regularizer": null, "units": 1}, "class_name": "Dense"}], "backend": "theano", "class_name": "Sequential", "keras_version": "2.0.3"}
+{"backend": "theano", "config": [{"config": {"name": "dense_1", "bias_constraint": null, "trainable": true, "dtype": "float32", "kernel_constraint": null, "units": 40, "batch_input_shape": [null, 79], "activation": "relu", "kernel_initializer": {"config": {"seed": null, "distribution": "uniform", "scale": 1.0, "mode": "fan_avg"}, "class_name": "VarianceScaling"}, "kernel_regularizer": null, "bias_regularizer": null, "use_bias": true, "activity_regularizer": null, "bias_initializer": {"config": {}, "class_name": "Zeros"}}, "class_name": "Dense"}, {"config": {"name": "dropout_1", "trainable": true, "rate": 0.5}, "class_name": "Dropout"}, {"config": {"name": "dense_2", "bias_constraint": null, "trainable": true, "kernel_constraint": null, "units": 40, "activation": "relu", "kernel_initializer": {"config": {"seed": null, "distribution": "uniform", "scale": 1.0, "mode": "fan_avg"}, "class_name": "VarianceScaling"}, "kernel_regularizer": null, "bias_regularizer": null, "use_bias": true, "activity_regularizer": null, "bias_initializer": {"config": {}, "class_name": "Zeros"}}, "class_name": "Dense"}, {"config": {"name": "dropout_2", "trainable": true, "rate": 0.5}, "class_name": "Dropout"}, {"config": {"name": "dense_3", "bias_constraint": null, "trainable": true, "kernel_constraint": null, "units": 5, "activation": "softmax", "kernel_initializer": {"config": {"seed": null, "distribution": "uniform", "scale": 1.0, "mode": "fan_avg"}, "class_name": "VarianceScaling"}, "kernel_regularizer": null, "bias_regularizer": null, "use_bias": true, "activity_regularizer": null, "bias_initializer": {"config": {}, "class_name": "Zeros"}}, "class_name": "Dense"}], "class_name": "Sequential", "keras_version": "2.0.3"}

MLPmodels/MLP.hidlay2.cells30.drop0.4.2class.json

@@ -1 +1 @@
-{"config": [{"config": {"bias_constraint": null, "dtype": "float32", "bias_regularizer": null, "bias_initializer": {"config": {}, "class_name": "Zeros"}, "trainable": true, "kernel_constraint": null, "batch_input_shape": [null, 79], "units": 30, "use_bias": true, "name": "dense_430", "kernel_regularizer": null, "activity_regularizer": null, "activation": "relu", "kernel_initializer": {"config": {"distribution": "uniform", "scale": 1.0, "mode": "fan_avg", "seed": null}, "class_name": "VarianceScaling"}}, "class_name": "Dense"}, {"config": {"name": "dropout_319", "trainable": true, "rate": 0.4}, "class_name": "Dropout"}, {"config": {"bias_constraint": null, "bias_initializer": {"config": {}, "class_name": "Zeros"}, "bias_regularizer": null, "trainable": true, "kernel_constraint": null, "units": 30, "use_bias": true, "name": "dense_431", "kernel_regularizer": null, "activity_regularizer": null, "activation": "relu", "kernel_initializer": {"config": {"distribution": "uniform", "scale": 1.0, "mode": "fan_avg", "seed": null}, "class_name": "VarianceScaling"}}, "class_name": "Dense"}, {"config": {"name": "dropout_320", "trainable": true, "rate": 0.4}, "class_name": "Dropout"}, {"config": {"bias_constraint": null, "bias_initializer": {"config": {}, "class_name": "Zeros"}, "bias_regularizer": null, "trainable": true, "kernel_constraint": null, "units": 30, "use_bias": true, "name": "dense_432", "kernel_regularizer": null, "activity_regularizer": null, "activation": "relu", "kernel_initializer": {"config": {"distribution": "uniform", "scale": 1.0, "mode": "fan_avg", "seed": null}, "class_name": "VarianceScaling"}}, "class_name": "Dense"}, {"config": {"name": "dropout_321", "trainable": true, "rate": 0.4}, "class_name": "Dropout"}, {"config": {"bias_constraint": null, "bias_initializer": {"config": {}, "class_name": "Zeros"}, "bias_regularizer": null, "trainable": true, "kernel_constraint": null, "units": 1, "use_bias": true, "name": "dense_433", "kernel_regularizer": null, "activity_regularizer": null, "activation": "sigmoid", "kernel_initializer": {"config": {"distribution": "uniform", "scale": 1.0, "mode": "fan_avg", "seed": null}, "class_name": "VarianceScaling"}}, "class_name": "Dense"}], "backend": "theano", "class_name": "Sequential", "keras_version": "2.0.3"}
+{"keras_version": "2.0.3", "class_name": "Sequential", "backend": "theano", "config": [{"class_name": "Dense", "config": {"use_bias": true, "dtype": "float32", "bias_initializer": {"class_name": "Zeros", "config": {}}, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"seed": null, "distribution": "uniform", "mode": "fan_avg", "scale": 1.0}}, "activity_regularizer": null, "bias_constraint": null, "trainable": true, "name": "dense_1", "kernel_constraint": null, "activation": "relu", "bias_regularizer": null, "batch_input_shape": [null, 79], "units": 30, "kernel_regularizer": null}}, {"class_name": "Dropout", "config": {"trainable": true, "rate": 0.4, "name": "dropout_1"}}, {"class_name": "Dense", "config": {"use_bias": true, "units": 30, "bias_initializer": {"class_name": "Zeros", "config": {}}, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"seed": null, "distribution": "uniform", "mode": "fan_avg", "scale": 1.0}}, "activity_regularizer": null, "bias_constraint": null, "trainable": true, "kernel_regularizer": null, "kernel_constraint": null, "bias_regularizer": null, "name": "dense_2", "activation": "relu"}}, {"class_name": "Dropout", "config": {"trainable": true, "rate": 0.4, "name": "dropout_2"}}, {"class_name": "Dense", "config": {"use_bias": true, "units": 30, "bias_initializer": {"class_name": "Zeros", "config": {}}, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"seed": null, "distribution": "uniform", "mode": "fan_avg", "scale": 1.0}}, "activity_regularizer": null, "bias_constraint": null, "trainable": true, "kernel_regularizer": null, "kernel_constraint": null, "bias_regularizer": null, "name": "dense_3", "activation": "relu"}}, {"class_name": "Dropout", "config": {"trainable": true, "rate": 0.4, "name": "dropout_3"}}, {"class_name": "Dense", "config": {"use_bias": true, "units": 5, "bias_initializer": {"class_name": "Zeros", "config": {}}, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"seed": null, "distribution": "uniform", "mode": "fan_avg", "scale": 1.0}}, "activity_regularizer": null, "bias_constraint": null, "trainable": true, "kernel_regularizer": null, "kernel_constraint": null, "bias_regularizer": null, "name": "dense_4", "activation": "softmax"}}]}

MLPmodels/MLP.hidlay4.cells40.drop0.5.2class.json

@@ -1 +1 @@
-{"config": [{"config": {"activation": "relu", "use_bias": true, "kernel_regularizer": null, "kernel_constraint": null, "name": "dense_4", "dtype": "float32", "batch_input_shape": [null, 79], "kernel_initializer": {"config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}, "class_name": "VarianceScaling"}, "bias_initializer": {"config": {}, "class_name": "Zeros"}, "trainable": true, "activity_regularizer": null, "bias_constraint": null, "bias_regularizer": null, "units": 40}, "class_name": "Dense"}, {"config": {"name": "dropout_3", "trainable": true, "rate": 0.5}, "class_name": "Dropout"}, {"config": {"activation": "relu", "use_bias": true, "kernel_constraint": null, "name": "dense_5", "bias_constraint": null, "kernel_initializer": {"config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}, "class_name": "VarianceScaling"}, "bias_initializer": {"config": {}, "class_name": "Zeros"}, "bias_regularizer": null, "trainable": true, "activity_regularizer": null, "kernel_regularizer": null, "units": 40}, "class_name": "Dense"}, {"config": {"name": "dropout_4", "trainable": true, "rate": 0.5}, "class_name": "Dropout"}, {"config": {"activation": "relu", "use_bias": true, "kernel_constraint": null, "name": "dense_6", "bias_constraint": null, "kernel_initializer": {"config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}, "class_name": "VarianceScaling"}, "bias_initializer": {"config": {}, "class_name": "Zeros"}, "bias_regularizer": null, "trainable": true, "activity_regularizer": null, "kernel_regularizer": null, "units": 40}, "class_name": "Dense"}, {"config": {"name": "dropout_5", "trainable": true, "rate": 0.5}, "class_name": "Dropout"}, {"config": {"activation": "relu", "use_bias": true, "kernel_constraint": null, "name": "dense_7", "bias_constraint": null, "kernel_initializer": {"config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}, "class_name": "VarianceScaling"}, "bias_initializer": {"config": {}, "class_name": "Zeros"}, "bias_regularizer": null, "trainable": true, "activity_regularizer": null, "kernel_regularizer": null, "units": 40}, "class_name": "Dense"}, {"config": {"name": "dropout_6", "trainable": true, "rate": 0.5}, "class_name": "Dropout"}, {"config": {"activation": "relu", "use_bias": true, "kernel_constraint": null, "name": "dense_8", "bias_constraint": null, "kernel_initializer": {"config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}, "class_name": "VarianceScaling"}, "bias_initializer": {"config": {}, "class_name": "Zeros"}, "bias_regularizer": null, "trainable": true, "activity_regularizer": null, "kernel_regularizer": null, "units": 40}, "class_name": "Dense"}, {"config": {"name": "dropout_7", "trainable": true, "rate": 0.5}, "class_name": "Dropout"}, {"config": {"activation": "sigmoid", "use_bias": true, "kernel_constraint": null, "name": "dense_9", "bias_constraint": null, "kernel_initializer": {"config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}, "class_name": "VarianceScaling"}, "bias_initializer": {"config": {}, "class_name": "Zeros"}, "bias_regularizer": null, "trainable": true, "activity_regularizer": null, "kernel_regularizer": null, "units": 1}, "class_name": "Dense"}], "backend": "theano", "class_name": "Sequential", "keras_version": "2.0.3"}
+{"class_name": "Sequential", "config": [{"class_name": "Dense", "config": {"name": "dense_1", "activation": "relu", "activity_regularizer": null, "bias_regularizer": null, "units": 40, "kernel_regularizer": null, "trainable": true, "use_bias": true, "bias_initializer": {"class_name": "Zeros", "config": {}}, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "bias_constraint": null, "batch_input_shape": [null, 79], "dtype": "float32"}}, {"class_name": "Dropout", "config": {"name": "dropout_1", "trainable": true, "rate": 0.5}}, {"class_name": "Dense", "config": {"name": "dense_2", "activation": "relu", "activity_regularizer": null, "units": 40, "kernel_regularizer": null, "trainable": true, "use_bias": true, "bias_regularizer": null, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}}}, {"class_name": "Dropout", "config": {"name": "dropout_2", "trainable": true, "rate": 0.5}}, {"class_name": "Dense", "config": {"name": "dense_3", "activation": "relu", "activity_regularizer": null, "units": 40, "kernel_regularizer": null, "trainable": true, "use_bias": true, "bias_regularizer": null, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}}}, {"class_name": "Dropout", "config": {"name": "dropout_3", "trainable": true, "rate": 0.5}}, {"class_name": "Dense", "config": {"name": "dense_4", "activation": "relu", "activity_regularizer": null, "units": 40, "kernel_regularizer": null, "trainable": true, "use_bias": true, "bias_regularizer": null, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}}}, {"class_name": "Dropout", "config": {"name": "dropout_4", "trainable": true, "rate": 0.5}}, {"class_name": "Dense", "config": {"name": "dense_5", "activation": "relu", "activity_regularizer": null, "units": 40, "kernel_regularizer": null, "trainable": true, "use_bias": true, "bias_regularizer": null, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}}}, {"class_name": "Dropout", "config": {"name": "dropout_5", "trainable": true, "rate": 0.5}}, {"class_name": "Dense", "config": {"name": "dense_6", "activation": "softmax", "activity_regularizer": null, "units": 5, "kernel_regularizer": null, "trainable": true, "use_bias": true, "bias_regularizer": null, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}}}], "keras_version": "2.0.3", "backend": "theano"}