arcin / ieee-fraud-detection

An example of logistic regression being used to detect fraud

ieee-fraud-detection

An example of logistic regression being used to detect fraud

Dataset

The kaggle dataset can be found here.

A couple of challenges with the dataset

1. The dataset uses PCA to hide sensitive information, making it difficult to understand what features have the best correlation with fraud.
2. There are a lot of missing values. Over Half of the hundreds of thousands of rows have missing data.
3. There is a large class imbalance. around 4 percent of the data is fraud.

Some approaches used in this solution

1. One-hot encoding categorical variables.
2. Filtering columns that have over 17% missing values.
3. Plotting distribution of null values to get an intuition of what columns may be important.