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Published May 12, 2019 | Version v0.16.0
Software Open

rasbt/mlxtend: Version 0.16.0

Authors/Creators

  • 1. UW-Madison
  • 2. @Quansight
  • 3. @infostellarinc
  • 4. @WIPACrepo
  • 5. Predikto Inc.
  • 6. IRIC @major-lab
  • 7. Michigan State University
  • 8. FANSI Motorsport
  • 9. Norwegian University of Life Sciences
  • 10. Easy Solutions
  • 11. Hospital IQ
  • 12. Textkernel
  • 13. @Lab41
  • 14. STM
  • 15. @spacetelescope
  • 16. Centre for Strategic Infocomm Technologies

Description

New Features
  • StackingCVClassifier and StackingCVRegressor now support random_state parameter, which, together with shuffle, controls the randomness in the cv splitting. (#523 via Qiang Gu)
  • StackingCVClassifier and StackingCVRegressor now have a new drop_last_proba parameter. It drops the last "probability" column in the feature set since if True,
      because it is redundant: p(y_c) = 1 - p(y_1) + p(y_2) + ... + p(y_{c-1}). This can be useful for meta-classifiers that are sensitive to perfectly collinear features. ([#532](https://github.com/rasbt/mlxtend/pull/532))
  • Other stacking estimators, including StackingClassifier, StackingCVClassifier and StackingRegressor, support grid search over the regressors and even a single base regressor. (#522 via Qiang Gu)
  • Adds multiprocessing support to StackingCVClassifier. (#522 via Qiang Gu)
  • Adds multiprocessing support to StackingCVRegressor. (#512 via Qiang Gu)
  • Now, the StackingCVRegressor also enables grid search over the regressors and even a single base regressor. When there are level-mixed parameters, GridSearchCV will try to replace hyperparameters in a top-down order (see the documentation for examples details). (#515 via Qiang Gu)
  • Adds a verbose parameter to apriori to show the current iteration number as well as the itemset size currently being sampled. (#519
  • Adds an optional class_name parameter to the confusion matrix function to display class names on the axis as tick marks. (#487 via sandpiturtle)
Changes
  • Due to new features, restructuring, and better scikit-learn support (for GridSearchCV, etc.) the StackingCVRegressor's meta regressor is now being accessed via 'meta_regressor__* in the parameter grid. E.g., if a RandomForestRegressor as meta- egressor was previously tuned via 'randomforestregressor__n_estimators', this has now changed to 'meta_regressor__n_estimators'. (#515 via Qiang Gu)
  • The same change mentioned above is now applied to other stacking estimators, including StackingClassifier, StackingCVClassifier and StackingRegressor. (#522 via Qiang Gu)
Bug Fixes
  • The feature_selection.ColumnSelector now also supports column names of type int (in addition to str names) if the input is a pandas DataFrame. (#500 via tetrar124
  • Fix unreadable labels in plot_confusion_matrix for imbalanced datasets if show_absolute=True and show_normed=True. (#504)
  • Raises a more informative error if a SparseDataFrame is passed to apriori and the dataframe has integer column names that don't start with 0 due to current limitations of the SparseDataFrame implementation in pandas. (#503)
  • SequentialFeatureSelector now supports DataFrame as input for all operating modes (forward/backward/floating). #506
  • mlxtend.evaluate.feature_importance_permutation now correctly accepts scoring functions with proper function signature as metric argument. #528

Files

rasbt/mlxtend-v0.16.0.zip

Files (41.5 MB)

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Additional details

Related works

Is supplement to
https://github.com/rasbt/mlxtend/tree/v0.16.0 (URL)