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PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #332

PROFESSIONAL-MACHINE-LEARNING-ENGINEER Question #332: Real Exam Question with Answer & Explanation

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Submitted by chen.hong· Apr 18, 2026ML model development

Question

You are developing a model to detect fraudulent credit card transactions. You need to prioritize detection, because missing even one fraudulent transaction could severely impact the credit card holder. You used AutoML to train a model on users' profile information and credit card transaction data. After training the initial model, you notice that the model is failing to detect many fraudulent transactions. How should you increase the number of fraudulent transactions that are detected?

Options

  • AAdd more non-fraudulent examples to the training set.
  • BReduce the maximum number of node hours for training.
  • CIncrease the probability threshold to classify a fraudulent transaction.
  • DDecrease the probability threshold to classify a fraudulent transaction.

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Topics

#Classification Threshold#Recall Optimization#Fraud Detection#Model Tuning
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