diff --git a/docs/release-notes/release-1.5.0.md b/docs/release-notes/release-1.5.0.md new file mode 100644 index 00000000..e5a2eded --- /dev/null +++ b/docs/release-notes/release-1.5.0.md @@ -0,0 +1,101 @@ +# [NimbusML](https://docs.microsoft.com/en-us/nimbusml/overview) 1.5.0 + +## **New Features** + +- **Initial implementation of `csr_matrix` output support.** + + [PR#250](https://github.com/microsoft/NimbusML/pull/250) + Add support for data output in `scipy.sparse.csr_matrix` format. + + ```python + xf = OneHotVectorizer(columns={'c0':'c0', 'c1':'c1'}) + xf.fit(train_df) + result = xf.transform(train_df, as_csr=True) + ``` + +- **Permutation Feature Importance for model interpretibility.** + + [PR#279](https://github.com/microsoft/NimbusML/pull/279) + Adds `permutation_feature_importance()` method to `Pipeline` and + predictor estimators, enabling evaluation of model-wide feature + importances on any dataset with same schema as the dataset used + to fit the `Pipeline`. + + ```python + pipe = Pipeline([ + LogisticRegressionBinaryClassifier(label='label', feature=['feature']) + ]) + pipe.fit(data) + pipe.permutation_feature_importance(data) + ``` + +- **Initial implementation of DateTime input and output column support.** + + [PR#290](https://github.com/microsoft/NimbusML/pull/290) + Add initial support for input and output of Pandas DateTime columns. + +- **Initial implementation of LpScaler.** + + [PR#253](https://github.com/microsoft/NimbusML/pull/253) + Normalize vectors (rows) individually by rescaling them to unit norm (L2, L1 or LInf). + Performs the following operation on a vector X: Y = (X - M) / D, where M is mean and D + is either L2 norm, L1 norm or LInf norm. + +- **Add support for variable length vector output.** + + [PR#267](https://github.com/microsoft/NimbusML/pull/267) + Support output of columns returned from ML.Net which contain variable length vectors. + +- **Save `predictor_model` when pickling a `Pipeline`.** + + [PR#295](https://github.com/microsoft/NimbusML/pull/295) + +- **Initial implementation of the WordTokenizer transform.** + + [PR#296](https://github.com/microsoft/NimbusML/pull/296) + +- **Add support for summary output from tree based predictors.** + + [PR#298](https://github.com/microsoft/NimbusML/pull/298) + +## **Bug Fixes** + +- **Fixed `Pipeline.transform()` in transform only `Pipeline` fails if y column is provided ** + + [PR#294](https://github.com/microsoft/NimbusML/pull/294) + Enable calling `.transform()` on a `Pipeline` containing only transforms when the y column is provided + +- **Fix issue when using `predict_proba` or `decision_function` with combined models.** + + [PR#272](https://github.com/microsoft/NimbusML/pull/272) + +- **Fix `Pipeline._extract_classes_from_headers` was not checking for valid steps.** + + [PR#292](https://github.com/microsoft/NimbusML/pull/292) + +- **Fix BinaryDataStream was not valid as input for transformer.** + + [PR#307](https://github.com/microsoft/NimbusML/pull/307) + +- **Fix casing for the installPythonPackages build.sh argument.** + + [PR#256](https://github.com/microsoft/NimbusML/pull/256) + +## **Breaking Changes** + +- **Removed `y` parameter from `Pipeline.transform()`** + + [PR#294](https://github.com/microsoft/NimbusML/pull/294) + Removed `y` parameter from `Pipeline.transform()` as it is not needed nor used for transforming data with a fitted `Pipeline`. + +## **Enhancements** + +None. + +## **Documentation and Samples** + +None. + +## **Remarks** + +None. diff --git a/release-next.md b/release-next.md index 031f060f..c6d1ec43 100644 --- a/release-next.md +++ b/release-next.md @@ -2,91 +2,11 @@ ## **New Features** -- **Initial implementation of `csr_matrix` output support.** - - [PR#250](https://github.com/microsoft/NimbusML/pull/250) - Add support for data output in `scipy.sparse.csr_matrix` format. - - ```python - xf = OneHotVectorizer(columns={'c0':'c0', 'c1':'c1'}) - xf.fit(train_df) - result = xf.transform(train_df, as_csr=True) - ``` - -- **Permutation Feature Importance for model interpretibility.** - - [PR#279](https://github.com/microsoft/NimbusML/pull/279) - Adds `permutation_feature_importance()` method to `Pipeline` and - predictor estimators, enabling evaluation of model-wide feature - importances on any dataset with same schema as the dataset used - to fit the `Pipeline`. - - ```python - pipe = Pipeline([ - LogisticRegressionBinaryClassifier(label='label', feature=['feature']) - ]) - pipe.fit(data) - pipe.permutation_feature_importance(data) - ``` - -- **Initial implementation of DateTime input and output column support.** - - [PR#290](https://github.com/microsoft/NimbusML/pull/290) - Add initial support for input and output of Pandas DateTime columns. - -- **Initial implementation of LpScaler.** - - [PR#253](https://github.com/microsoft/NimbusML/pull/253) - Normalize vectors (rows) individually by rescaling them to unit norm (L2, L1 or LInf). - Performs the following operation on a vector X: Y = (X - M) / D, where M is mean and D - is either L2 norm, L1 norm or LInf norm. - -- **Add support for variable length vector output.** - - [PR#267](https://github.com/microsoft/NimbusML/pull/267) - Support output of columns returned from ML.Net which contain variable length vectors. - -- **Save `predictor_model` when pickling a `Pipeline`.** - - [PR#295](https://github.com/microsoft/NimbusML/pull/295) - -- **Initial implementation of the WordTokenizer transform.** - - [PR#296](https://github.com/microsoft/NimbusML/pull/296) - -- **Add support for summary output from tree based predictors.** - - [PR#298](https://github.com/microsoft/NimbusML/pull/298) +None. ## **Bug Fixes** -- **Fixed `Pipeline.transform()` in transform only `Pipeline` fails if y column is provided ** - - [PR#294](https://github.com/microsoft/NimbusML/pull/294) - Enable calling `.transform()` on a `Pipeline` containing only transforms when the y column is provided - -- **Fix issue when using `predict_proba` or `decision_function` with combined models.** - - [PR#272](https://github.com/microsoft/NimbusML/pull/272) - -- **Fix `Pipeline._extract_classes_from_headers` was not checking for valid steps.** - - [PR#292](https://github.com/microsoft/NimbusML/pull/292) - -- **Fix BinaryDataStream was not valid as input for transformer.** - - [PR#307](https://github.com/microsoft/NimbusML/pull/307) - -- **Fix casing for the installPythonPackages build.sh argument.** - - [PR#256](https://github.com/microsoft/NimbusML/pull/256) - -## **Breaking Changes** - -- **Removed `y` parameter from `Pipeline.transform()`** - - [PR#294](https://github.com/microsoft/NimbusML/pull/294) - Removed `y` parameter from `Pipeline.transform()` as it is not needed nor used for transforming data with a fitted `Pipeline`. +None. ## **Enhancements**