Change Logs

0.5.1

  • #130 numpy 2.0

  • #132 builds against scikit-learn==1.5.0, python 3.12

0.5.0

  • #118 major refactoring, changes CI, builds against scikit-learn 1.3

  • #115 Updates tree decision criterion for scikit-learn 1.2 (2023-07-02)

  • #113 Removes normalize attributes (deprecated) (2022-11-29)

  • #110 Fixes perplexity issue with PredictableTSNE (2022-08-06)

  • #109 Use f strings in more places (2022-07-22)

0.3.649 - 2022-07-22 - 2.35Mb

  • #105 Update for python 3.10 (2022-07-22)

  • #108 Uses f strings (2022-07-19)

0.3.631 - 2022-05-19 - 2.21Mb

  • #107 Updates CI for scikit-learn==1.1 (2022-05-18)

  • #106 Fixes failing import _joblib_parallel_args (2022-02-18)

  • #99 LICENSE file missing in PyPI release (2021-11-20)

0.3.614 - 2021-10-02 - 1.73Mb

  • #103 Updates for scikit-learn>=1.0 (2021-10-02)

  • #94 Fixed Numpy boolean array indexing issue for 2dim arrays. (2021-09-27)

0.3.606 - 2021-08-22 - 2.35Mb

  • #102 Implements numpy.digitalize with a DecisionTreeRegressor (2021-08-22)

  • #101 Update CI to build manylinux for python 3.9 (2021-08-18)

  • #100 Support parameter positive for QuantileLinearRegression (2021-06-23)

  • #96 Fixes #95, PiecewiseRegressor, makes sure target are vectors (2021-05-27)

  • #95 _apply_prediction_method boolean indexing incompatible with standard sklearn format (2021-05-27)

  • #80 Piecewise Estimator` binner not a decision tree (2021-05-06)

  • #72 Optimal decission tree for piecewise estimator (2021-05-06)

  • #98 Fixes #97, fix issue with deepcopy and criterion (2021-05-03)

  • #97 piecewise_decision_tree does not compile with the latest version of scikit-learn (2021-05-03)

  • #85 Fixes #70, implements DecisionTreeLogisticRegression (2021-05-02)

  • #93 Include build wheel for all platforms in CI (2021-01-09)

  • #89 Install fails` ModuleNotFoundError` No module named ‘sklearn’ (2021-01-03)

  • #92 QuantileMLPRegressor does not work with scikit-learn 0.24 (2021-01-01)

  • #91 Fixes regression criterion for scikit-learn 0.24 (2021-01-01)

  • #90 Fixes PipelineCache for scikit-learn 0.24 (2021-01-01)

  • #88 Change for scikit-learn 0.24 (2020-09-02)

  • #87 Set up CI with Azure Pipelines (2020-09-02)

  • #86 Update CI, use python 3.8 (2020-09-02)

  • #71 update kmeans l1 to the latest kmeans (signatures changed) (2020-08-31)

  • #84 style (2020-08-30)

  • #83 Upgrade version (2020-08-06)

  • #82 Fixes #81, skl 0.22, 0.23 together (2020-08-06)

  • #81 Make mlinsights work with scikit-learn 0.22 and 0.23 (2020-08-06)

  • #79 pipeline2dot fails with ‘passthrough’ (2020-07-16)

  • #78 Removes strong dependency on pyquickhelper (2020-06-29)

  • #77 Add parameter trainable to TransferTransformer (2020-06-07)

  • #76 ConstraintKMeans does not produce convex clusters. (2020-06-03)

  • #75 Moves kmeans with constraint from papierstat. (2020-05-27)

  • #74 Fix PipelineCache after as scikti-learn 0.23 changed the way parameters is handle in pipelines (2020-05-15)

  • #73 ClassifierKMeans.__repr__ fails with scikit-learn 0.23 (2020-05-14)

  • #69 Optimizes k-means with norm L1 (2020-01-13)

  • #66 Fix visualisation graph` does not work when column index is an integer in ColumnTransformer (2019-09-15)

  • #59 Add GaussianProcesses to the notebook about confidence interval and regression (2019-09-15)

  • #65 Implements a TargetTransformClassifier similar to TargetTransformRegressor (2019-08-24)

  • #64 Implements a different version of TargetTransformRegressor which includes predefined functions (2019-08-24)

  • #63 Add a transform which transform the target and applies the inverse function of the prediction before scoring (2019-08-24)

  • #49 fix menu in documentation (2019-08-24)

  • #61 Fix bug in pipeline2dot when keyword “passthrough is used” (2019-07-11)

  • #60 Fix visualisation of pipeline which contains string “passthrough” (2019-07-09)

  • #58 Explores a way to compute recommandations without training (2019-06-05)

  • #56 Fixes #55, explore caching for scikit-learn pipeline (2019-05-22)

  • #55 Explore caching for gridsearchCV (2019-05-22)

  • #53 implements a function to extract intermediate model outputs within a pipeline (2019-05-07)

  • #51 Implements a tfidfvectorizer which keeps more information about n-grams (2019-04-26)

  • #46 implements a way to determine close leaves in a decision tree (2019-04-01)

  • #44 implements a model which produces confidence intervals based on bootstrapping (2019-03-29)

  • #40 implements a custom criterion for a decision tree optimizing for a linear regression (2019-03-28)

  • #39 implements a custom criterion for decision tree (2019-03-26)

  • #41 implements a direct call to a lapack function from cython (2019-03-25)

  • #38 better implementation of a regression criterion (2019-03-25)

  • #37 implements interaction_only for polynomial features (2019-02-26)

  • #36 add parameter include_bias to extended features (2019-02-25)

  • #34 rename PiecewiseLinearRegression into PiecewiseRegression (2019-02-23)

  • #33 implement the piecewise classifier (2019-02-23)

  • #31 uses joblib for piecewise linear regression (2019-02-23)

  • #30 explore transpose matrix before computing the polynomial features (2019-02-17)

  • #29 explore different implementation of polynomialfeatures (2019-02-15)

  • #28 implement PiecewiseLinearRegression (2019-02-10)

  • #27 implement TransferTransformer (2019-02-04)

  • #26 add function to convert a scikit-learn pipeline into a graph (2019-02-01)

  • #25 implements kind of trainable t-SNE (2019-01-31)

  • #6 use keras and pytorch (2019-01-03)

  • #22 modifies plot gallery to impose coordinates (2018-11-10)

  • #20 implements a QuantileMLPRegressor (quantile regression with MLP) (2018-10-22)

  • #19 fix issues introduced with changes in keras 2.2.4 (2018-10-06)

  • #18 remove warning from scikit-learn about cloning (2018-09-16)

  • #16 move CI to python 3.7 (2018-08-21)

  • #17 replace as_matrix by values (pandas deprecated warning) (2018-07-29)

  • #14 add transform to convert a learner into a transform (sometimes called a featurizer) (2018-06-19)

  • #13 add transform to do model stacking (2018-06-19)

  • #8 move items from papierstat (2018-06-19)

  • #12 fix bug in quantile regression` wrong weight for linear regression (2018-06-16)

  • #11 specifying quantile (2018-06-16)

  • #4 add function to compute non linear correlations (2018-06-16)

  • #10 implements combination between logistic regression and k-means (2018-05-27)

  • #9 move items from ensae_teaching_cs (2018-05-08)

  • #7 add quantile regression (2018-05-07)

  • #5 replace flake8 by code style (2018-04-14)

  • #1 change background for cells in notebooks converted into rst then in html, highlight-ipython3 (2018-01-05)

  • #2 save features and metadatas for the search engine and retrieves them (2017-12-03)