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PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #34

PROFESSIONAL-MACHINE-LEARNING-ENGINEER Question #34: Real Exam Question with Answer & Explanation

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Submitted by neha2k· Apr 18, 2026Data processing and feature engineering

Question

You were asked to investigate failures of a production line component based on sensor readings. After receiving the dataset, you discover that less than 1% of the readings are positive examples representing failure incidents. You have tried to train several classification models, but none of them converge. How should you resolve the class imbalance problem?

Options

  • AUse the class distribution to generate 10% positive examples.
  • BUse a convolutional neural network with max pooling and softmax activation.
  • CDownsample the data with upweighting to create a sample with 10% positive examples.
  • DRemove negative examples until the numbers of positive and negative examples are equal.

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Topics

#Class Imbalance#Data Resampling#Class Weighting#Data Preprocessing
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