Ctrl+K

Release notes#

1.0.7#

Released on 2024-04-15 - GitHub - PyPI

Enhancements

  • Add compatibility with latest changes in scikit-learn 1.4+ (#54)

1.0.6#

Released on 2023-11-22 - GitHub - PyPI

Enhancements

  • Added support for auto detection from byte file-like objects (#53).

Bugfixes

  • Ensure to reseek before loading segmentation models if needed. This could cause unexpected crashes when auto detecting random forest pmml files (a4bed07).

1.0.5#

Released on 2023-11-05 - GitHub - PyPI

Enhancements

  • Add support for non-seekable file-like objects (d0c0034)

Bugfixes

  • Fix for loading file-like objects directly instead of providing a file path; caused a file already closed error (55de16a)

1.0.4#

Released on 2023-11-01 - GitHub - PyPI

Enhancements

  • 🌟Added method to automatically detect the model type from the PMML file, and return the corresponding scikit-learn model (#51).

1.0.3#

Released on 2023-07-16 - GitHub - PyPI

Bugfixes

  • Fix typo that caused memory leak using tree based models (#50)

1.0.2#

Released on 2023-04-25 - GitHub - PyPI

Bugfixes

  • Fix for building on Apple Silicon (83519d9)
  • Several changes to make sklearn-pmml-model work with the latest versions of scikit-learn.

1.0.1#

Released on 2022-08-15 - GitHub - PyPI

Bugfixes

  • Correctly retrieve votes distribution for float target trees (#45)

1.0.0#

Released on 2022-02-03 - GitHub - PyPI

All major estimator types which are supported in both PMML and scikit-learn are now supported!

0.0.22#

Released on 2022-01-29 - GitHub - PyPI

Enhancements

  • 🌟Added support for multi-layer perceptron estimators PMMLMLPClassifier and PMMLMLPRegressor (#40).

0.0.21#

Released on 2022-01-24 - GitHub - PyPI

Bugfixes

  • Improved compatibility with scikit-learn major release 1.0 (#37).

Enhancements

  • 🌟Added support for k-nearest neighbor estimators PMMLKNeighborsClassifier and PMMLKNeighborsRegressor (#38).

0.0.20#

Released on 2021-09-07 - GitHub - PyPI

Enhancements

  • Support one-vs-rest logistic regression models (#36)

0.0.19#

Released on 2021-07-27 - GitHub - PyPI

Enhancements

  • Updated automatic wheel building on CI to use GitHub Actions (#33)

0.0.18#

Released on 2021-07-27 - GitHub - PyPI

Bugfixes

  • Fixed a problem that could block logistic regression from working in new versions of scikit-learn (4b6e11c).
  • The input array shape now gets validated, and pandas dataframes gets subscripted and reordered to match the PMML file (2555898).

Enhancements

  • 🌟Added support for support vector machine classification and regression (#31).
  • Several improvements to documentation and code style.

0.0.17#

Released on 2021-06-16 - GitHub - PyPI

Bugfixes

  • Fixed an issue with categorical features that occurred when categories contained spaces.

Enhancements

  • 🌟Added support for tree-based regression, including decision trees (PMMLTreeRegressor), random forests (PMMLForestRegressor) and gradient boosting (PMMLGradientBoostingRegressor) (#25).
  • Added support for classification with linear models, with PMMLLogisticRegression for regression models, and PMMLRidgeClassifier for general regression models (#24).

0.0.16#

Released on 2021-05-26 - GitHub - PyPI

Bugfixes

  • Fix compatibility issues with the latest version of scikit-learn
  • prevent inheritance problem related to _more_tags property

Enhancements

  • 🌟Support gradient boosting classifiers, including categorical features (#20)
  • Add an example that highlights the usage of tree.decision_path

0.0.15#

Released on 2020-08-18 - GitHub - PyPI

Bugfixes

  • Correctly parse ensemble trees with only a subset of target features. This happened to be the case for certain PMML models created with MatLab (#21)

0.0.14.1#

Released on 2020-08-18 - GitHub - PyPI

Bugfixes

  • Prevent Buffer dtype mismatch on 64 bit windows (reported in #19)

0.0.14#

Released on 2020-07-22 - GitHub - PyPI

Bugfixes

  • LocalTransformations are now parsed rather than only the global TransformationDictionary

Enhancements

  • Added support for multiSplit decision trees
  • Support average multipleModelStrategy for Random Forests

0.0.13#

Released on 2020-03-24 - GitHub - PyPI

Bugfixes

  • Ensures compatibility with the latest scikit-learn versions.

0.0.12#

Released on 2020-03-24 - GitHub - PyPI

Bugfixes

  • Define a minimum numpy version to ensure the library is compatible. Fixes issue #18.

0.0.11#

Released on 2020-03-24 - GitHub - PyPI

Enhancements

  • Added support for Naive Bayes models
  • Automatically build wheels on CI to make the installation from pip easier: no c compiler is required, which is especially useful on windows.

0.0.10#

Released on 2019-10-14 - GitHub - PyPI

Bugfixes

  • Fixes output for tree_.threshold for categorical trees. This is useful for inspecting decision trees, as done in this sklearn example. Thanks to @kodonnell for reporting!
On this page
Show Source