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Features selection algorithm based on self selected algorithm, loss function and validation method

Project description

License: MIT PyPI version

General features selection based on certain machine learning algorithm and evaluation methods

Divesity, Flexible and Easy to use

More features selection method will be included in the future!

Quick Installation

pip3 install MLFeatureSelection

Modulus in version

  • Modulus for selecting features based on greedy algorithm (from MLFeatureSelection import sequence_selection)
  • Modulus for removing features based on features importance (from MLFeatureSelection import importance_selection)
  • Modulus for removing features based on correlation coefficient (from MLFeatureSelection import coherence_selection)
  • Modulus for reading the features combination from log file (from import readlog)

Modulus Usage


This features selection method achieved

  • 1st in Rong360

  • 6th in JData-2018

  • 12nd in IJCAI-2018 1st round


More examples are added in example folder include:

  • Demo contain all modulus can be found here (demo)
  • Simple Titanic with 5-fold validation and evaluated by accuracy (demo)
  • Demo for S1, S2 score improvement in JData 2018 predict purchase time competition (demo)
  • Demo for IJCAI 2018 CTR prediction (demo)

Function Parameters


Algorithm details


Project details

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