This repository contains the final report for the Data Mining course (IS252.O21) in UIT. The report explores various data mining techniques, including preprocessing, classification, clustering, and association rule mining.
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The study focuses on the application of data mining methods in real-world scenarios. It covers:
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Data Preprocessing: Handling missing values, data normalization, and feature selection.
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Classification Techniques: Implementing and evaluating machine learning models such as Decision Trees, Naive Bayes, KNN.
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Association Rule Mining: Extracting meaningful patterns using Apriori and FP-Growth algorithms.
The report also includes experimental results, performance evaluation, and insights into the effectiveness of different techniques.
Python (Pandas, Scikit-learn, TensorFlow)
Jupyter Notebook