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Published February 14, 2017 | Version v0.5.1
Software Open

rasbt/mlxtend: Version 0.5.1

Authors/Creators

  • 1. Michigan State University
  • 2. Predikto Inc.
  • 3. FANSI Motorsport
  • 4. Easy Solutions
  • 5. @adobe-platform
  • 6. LPI ASC
  • 7. @betteroutcomes

Description

Version 0.5.1 (2017-02-14)

The CHANGELOG for the current development version is available at https://github.com/rasbt/mlxtend/blob/master/docs/sources/CHANGELOG.md.

Downloads New Features
  • The EnsembleVoteClassifier has a new refit attribute that prevents refitting classifiers if refit=False to save computational time.
  • Added a new lift_score function in evaluate to compute lift score (via Batuhan Bardak).
  • StackingClassifier and StackingRegressor support multivariate targets if the underlying models do (via kernc).
  • StackingClassifier has a new use_features_in_secondary attribute like StackingCVClassifier.
Changes
  • Changed default verbosity level in SequentialFeatureSelector to 0
  • The EnsembleVoteClassifier now raises a NotFittedError if the estimator wasn't fit before calling predict. (via Anton Loss)
  • Added new TensorFlow variable initialization syntax to guarantee compatibility with TensorFlow 1.0
Bug Fixes
  • Fixed wrong default value for k_features in SequentialFeatureSelector
  • Cast selected feature subsets in the SequentialFeautureSelector as sets to prevent the iterator from getting stuck if the k_idx are different permutations of the same combination (via Zac Wellmer).
  • Fixed an issue with learning curves that caused the performance metrics to be reversed (via ipashchenko)
  • Fixed a bug that could occur in the SequentialFeatureSelector if there are similarly-well performing subsets in the floating variants (via Zac Wellmer).

Files

rasbt/mlxtend-v0.5.1.zip

Files (11.9 MB)

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Additional details

Related works

Is supplement to
https://github.com/rasbt/mlxtend/tree/v0.5.1 (URL)