This is an end to end machine learning project using my personal shopping data collected over the past three years.
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Updated
Sep 1, 2023 - Jupyter Notebook
This is an end to end machine learning project using my personal shopping data collected over the past three years.
This repository focuses on credit card fraud detection using machine learning models, addressing class imbalance with SMOTE & undersampling, and optimizing performance via Grid Search & RandomizedSearchCV. It explores Logistic Regression, Random Forest, Voting Classifier, and XGBoost. balancing precision-recall trade-offs for fraud detection.
A comprehensive machine learning(binary classification) project for detecting credit fraud on a highly imbalanced dataset.
Stroke prediction using machine learning (LogReg, RF, GBoost, LightGBM) with class imbalance handling and threshold optimisation
Identifying rare event.
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