Collection of open machine learning papers

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Feature selection (variable selection)

Feature selection is the process of selecting a subset of relevant features (variables, predictors) for use in model construction (Wikipedia)

Why feature selection?

  1. Data exploration
  2. Curse of dimensionality
  3. Less features - faster models
  4. Better metrics

Filter methods

Filter methods use model-free ranking to filter less relevant features

Wrapper methods

Wrapper methods use a model and its performance to find the best feature subset

Embedded methods

Unsupervised and semi-supervised feature selection

Stable feature selection


Meta feature selection


Star Issue