Interview Q&A / Machine Learning
Machine Learning interview questions
Supervised vs unsupervised learning, overfitting, metrics and the classic models, explained simply.
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- How do class weights, oversampling and undersampling differ for imbalanced data?
Class weights make mistakes on the rare class cost more during training. Oversampling duplicates or synthesises minority rows; undersampling removes majority rows. Weights change no data, oversampling can overfit, undersampling can throw away useful rows.
IntermediateQuick answer1 min read