GitHub / rhsbd / Credit-Card-Fraud-Detection-on-Imbalanced-Data-Using-Machine-Learning

A Jupyter notebook that applies machine learning techniques to detect credit card fraud on imbalanced data. It covers data preprocessing, EDA, handling class imbalance, training classifiers (Logistic Regression, Decision Tree, RandomForest), and saving the trained models.

JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rhsbd%2FCredit-Card-Fraud-Detection-on-Imbalanced-Data-Using-Machine-Learning

Topics: decision-tree, imbalanced-data, logistic-regression, machine-learning, random-forest-classifier

• Files
• Readme
• Dependencies