History#

current - 2022-07-22 - 0.00Mb#

0.3.631 - 2022-05-19 - 0.52Mb#

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

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

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

0.3.614 - 2021-10-02 - 0.52Mb#

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

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

0.3.606 - 2021-08-22 - 0.52Mb#

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

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

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

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

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

  • issue 80: Piecewise Estimator: binner not a decision tree (2021-05-06)

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

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

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

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

0.3.549 - 2021-01-09 - 0.67Mb#

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

0.3.543 - 2021-01-03 - 0.67Mb#

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

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

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

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

0.2.508 - 2020-09-02 - 0.43Mb#

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

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

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

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

  • issue 84: style (2020-08-30)

0.2.491 - 2020-08-06 - 0.83Mb#

  • issue 83: Upgrade version (2020-08-06)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

  • issue 28: implement PiecewiseLinearRegression (2019-02-10)

  • issue 27: implement TransferTransformer (2019-02-04)

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

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

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

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

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

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

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

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

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

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

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

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

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

  • issue 11: specifying quantile (2018-06-16)

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

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

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

  • issue 7: add quantile regression (2018-05-07)

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

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

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