A machine learning model to detect suspicious credit card activities, which is a frequent issue companies have to deal with.

To address this problem, I used a public data set. The source was kept unrevealed due to privacy policies.

You can find the data in a csv file attached to this repository in the database folder. If it was helpful to you, you could give it a ⭐

This type of statistical model is used for classification and predictive analysis. Estimate the probability of a binary-outcome event occurring given a dataset of independent variables.

For this study case, I used the following independent variables:

• distance from home
• distance from the last transaction
• median purchase price and current purchase price ratio
• repeat retailer (yes or not)
• used chip (yes or not)
• used pin number (yes or not)
• online order (yes or not)

Model accuracy: 94.0 %

In this stage, I tuned the hyperparameters optimizing the model. By using GridSearchCV we find the best combination which result in the highest accuracy.