What Cross-Validation Reduces: Bias, Variance, Type I or Type II Error
Company: Headlands
Role: Data Scientist
Category: Machine Learning
Difficulty: medium
Interview Round: Online Assessment
Overview: A multiple-choice question asking whether cross-validation reduces bias, variance, Type I error or Type II error, with a justification for the choice. It tests what cross-validation actually estimates, how fold count trades bias against variance of the estimate, and how it differs from hypothesis-testing error rates.
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