Data Analysis Using Python
CurrentTo identify the best model for identifying transaction anomalies and potentially fraudulent cases, a variety of machine learning techniques, including data cleaning, exploratory data analysis, and Random Forest, SVM, KNN, Decision Tree, Gaussian Naïve Bayes, and Logistic Regression, were employed. The finished Random Forest model had 99.96% accuracy using.