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Published December 22, 2017 | Version v0.10.0
Software Open

rasbt/mlxtend: Version 0.10.0

Authors/Creators

  • 1. Michigan State University
  • 2. @infostellarinc
  • 3. Predikto Inc.
  • 4. @WIPACrepo
  • 5. FANSI Motorsport
  • 6. Easy Solutions
  • 7. @adobe-platform
  • 8. @Workable
  • 9. LPI ASC
  • 10. Saarland University
  • 11. millesime.ai
  • 12. @betteroutcomes
  • 13. Trifork
  • 14. STM

Description

New Features
  • New store_train_meta_features parameter for fit in StackingCVRegressor. if True, train meta-features are stored in self.train_meta_features_. New pred_meta_features method for StackingCVRegressor. People can get test meta-features using this method. (#294 via takashioya)
  • The new store_train_meta_features attribute and pred_meta_features method for the StackingCVRegressor were also added to the StackingRegressor, StackingClassifier, and StackingCVClassifier (#299 & #300)
  • New function (evaluate.mcnemar_tables) for creating multiple 2x2 contigency from model predictions arrays that can be used in multiple McNemar (post-hoc) tests or Cochran's Q or F tests, etc. (#307)
  • New function (evaluate.cochrans_q) for performing Cochran's Q test to compare the accuracy of multiple classifiers. (#310)
Changes Bug Fixes
  • Improved numerical stability for p-values computed via the the exact McNemar test (#306)
  • nose is not required to use the library (#302)

Files

rasbt/mlxtend-v0.10.0.zip

Files (10.6 MB)

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md5:00fa127a24bf0189810dfabdffa7db32
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Additional details

Related works

Is supplement to
https://github.com/rasbt/mlxtend/tree/v0.10.0 (URL)