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PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #164

PROFESSIONAL-MACHINE-LEARNING-ENGINEER Question #164: Real Exam Question with Answer & Explanation

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Submitted by viktor_hu· Apr 18, 2026Data processing and feature engineering

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?

Options

  • AModify the target variable using the Box-Cox transformation.
  • BZ-normalize all the numeric features.
  • COversample the fraudulent transaction 10 times.
  • DLog transform all numeric features.

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Topics

#Class Imbalance#Oversampling#Data Preprocessing#Random Forest
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