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EE6227-ML-Assignment

NTU EE7226 Genetic Algorithm & Machine Learning - Machine Learning Part

Assignment Description

  • Assignment 1: Train 3 classifiers, Bayes Decision Rule, Naive Bayes and Linear Discriminant Analysis(LDA), on the given dataset. Then give prediction on the test set.
  • Assignment 2: Train a binary classification tree for a given dataset, utlizing some data preprocessing techniques for missing values and outliers. Then give prediction on the test set.

Please Find more details for assignment requirements in the Assignment-1-classifiers/Ass1.pdf and Assignment-2-classification_tree/Ass2.pdf.

Repository Overview

  • Assignment-1-classifiers/:
    • data/: Training and test set in .mat format.
    • poc_classifier.ipynb: Proof of concept for the classifiers.
    • main.py: Generated py file from the notebook.
    • results/: Results of the classifiers, .csv and .mat format.
  • Assignment-2-classification_tree/:
    • data/: Training and test set in .xlsx format.
    • preprocess/: Preprocessed training set, .xlsx format.
      • add_head.xlsx: Orignal training set with added head.
      • sto_cap_train.xlsx: Stocasitcally imputed + capped training set.
    • preprocess.ipynb: Data preprocessing for the training set.
    • class_tree.ipynb: Handmade binary classification tree.
    • results/: Results of the classifiers, .xlsx format.
    • backup/: Backup file for pre-puring in classfication tree.
  • submission/: submission files for both assignments.
  • README.md: This file.
  • requirements.txt: List of packages required to run the code.

Environment

The packages are listed in requirements.txt. To create a conda environment with the packages, run the following command:

conda create --name your_env_name --file requirements.txt

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