1.

Explain Features Selection.

Answer»

During processing, Big data may contain a large amount of data that is not REQUIRED at a particular time, So we may be required to select only some specific features that we are interested in. The PROCESS of extracting only the needed features from the Big data is called FEATURE selection.

Feature selection Methods are -

  • Filters Method: In this method of variable ranking, we only consider the importance and usefulness of a feature.
  • Wrappers Method: In this method, ‘INDUCTION algorithm’ is used, Which can be used to produce a classifier.
  • Embedded Method: This method is a combination of EFFICIENCIES of both Filters and wrappers methods.


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