Model Training

Once the data has been prepared, the Logistic Regression algorithm is trained using the training dataset.

During training, the model learns relationships between the transaction features and the corresponding transaction class.

The objective is to identify patterns that distinguish fraudulent transactions from legitimate ones.

A well-trained model should correctly classify new transactions that were not part of the training dataset.