The Three Edge Case Culprits: Bias, Variance, and Unpredictability
Edge cases occur for three basic reasons: Bias – the ML system is too ‘simple’; Variance – the ML system is too ‘inexperienced’; Unpredictability – the ML system operates in an environment full of surprises. How do we recognize these edge cases situations, and what can we do about them?
By iMerit on Apr 22, 2021 in
Bias, iMerit, Machine Learning, Variance