Project Structure

• EDA & preprocessing: Exploratory Data Analysis and data preprocessing
• Model: Implementation of different models (Naive Bayes, Logistic Regression, XGBoost, Neural Network)
• Testing: Model evaluation and performance metrics
• Explainability: Feature importance analysis for different models

Running the Code

Data Exploration:

Run EDA & preprocessing/EDA.ipynb for data analysis

Data Preprocessing:

Run preprocessing/train_test_split.py

Model Training:

• Naive Bayes: Model/nb.py
• Logistic Regression: Model/lr.py
• XGBoost:
  • For local execution: Model/xgb.py
  • For SCC batch job, see: Model/xgb.sh
• Neural Network:
  • For local execution: Model/nn.py
  • For SCC batch job, see: Model/nn.sh

Model Testing:

Run Testing/testing.ipynb

Explainability Analysis:

Run Explainability/explainability.ipynb