For questions related to feature engineering, which is the process of using domain knowledge to extract features from raw data via data mining techniques.
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Why are decision trees and random forests scale invariant?How to perform prediction when some features have missing values?
When is it necessary to manually extract features to feed into the neural network rather than providing raw data?
When is it necessary to manually extract features to feed into the neural network rather than providing raw data?
Does feature scaling have any benefits if all features are on the same scale?
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