bking2415 / detect-credit-card-fraud

Implemented machine learning algorithms to detect credit card fraud in Python

Detect Credit Card Fraud

Implemented machine learning algorithms to detect credit card fraud in Python

Instructions

1. Make sure all the proper libraries are imported (i.e pandas, numpy, sklearn) and packages are installed.
2. Run fraudDetect.py to run the different machine learning algorithms.

Key Machine Learning Algorithms

Machine Learning Algorithms concepts used in the code. Listed Below:

• General Logistic Regression Model: Logistic regression is used for modeling the outcome probability of a class such as pass/fail.
• Decision Tree: Decision tree algorithm to plot the outcome of a decision using entropy or GINI Index.
• MLP(Multi-layer Perceptron): Learn the patterns using the historical data and are able to perform classification on the input data.
• Gradient Boosting (GBM): A machine learning technique for regression and classification problems.

Project Structure

• fraudDetect.py -- The implementation of the machine learning algorithms on the train and test set.
• createFormula.py -- Module to create the function used in the logistic regression model.
• fraud.png -- Output of the decision tree created by the model.

Results

Sample Output:

Decision Tree: