Credit card fraud detection using data analysis
For the Data Science capstone project, I aim to detect credit card fraud using supervised data analysis. This proposal details plans for a program to detect fraudulent activities of credit cards. The program will use a Random Forest Decision Tree (RFDT) to classify and distinguish between fraudulent activities and authentic ones. RFDT is a machine learning method that trains the program and the model to derive conclusions. A decision is derived when the majority vote of decision trees and branches points to one conclusion. RFDT often consists of multiple branches of decisions, and the algorithm ultimately produces the decision that is the strongest.