💳 Credit Card Fraud Detection

🎯 Objective

Detect fraudulent credit card transactions (Class = 1) using machine learning.
The project focuses on accurate identification of fraud in a highly imbalanced dataset.

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🧠 Overview

This project employs a Random Forest Classifier optimized with RandomizedSearchCV.
Key points:

• Handles imbalanced data effectively
• Provides probability scores for fraud prediction
• Threshold adjustment available for recall optimization

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🔍 Data Preprocessing & EDA

• Checked for missing values and duplicates
• Selected Class as the target column
• Split data into training and testing sets
• Visualized distributions and relationships using scatter plots, line plots, KDE, and boxplots

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🛠️ Technologies

• 🐍 Python 3
• 📊 pandas, numpy for data handling
• 📈 matplotlib, seaborn for visualization
• 🤖 scikit-learn for modeling
• 📓 Jupyter Notebook for interactive analysis
• 🌐 GitHub: Mehdipoladrag
• 🏆 Kaggle: mehdip1