NTU EE7226 Genetic Algorithm & Machine Learning - Machine Learning Part
- 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
.
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.
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