You work for a bank and are building a random forest model for fraud detection. You have a dataset that includes transactions, of which 1% are identified as fraudulent. Which data transformation strategy would likely improve the performance of your classifier?
A) Write your data in TFRecords.
B) Z-normalize all the numeric features.
C) Oversample the fraudulent transaction 10 times.
D) Use one-hot encoding on all categorical features.

Question

You work for a bank and are building a random forest model for fraud detection. You have a dataset that includes transactions, of which 1% are identified as fraudulent. Which data transformation strategy would likely improve the performance of your classifier?
A) Write your data in TFRecords.
B) Z-normalize all the numeric features.
C) Oversample the fraudulent transaction 10 times.
D) Use one-hot encoding on all categorical features.

Quizplus · Accepted Answer

Oversampling the fraudulent transactions will help balance the dataset, which is important for improving the performance of classifiers on imbalanced datasets like fraud detection.

You Work for a Bank and Are Building a Random