diff --git a/docs/release-notes/release-1.4.0.md b/docs/release-notes/release-1.4.0.md new file mode 100644 index 00000000..1c30e978 --- /dev/null +++ b/docs/release-notes/release-1.4.0.md @@ -0,0 +1,57 @@ +# [NimbusML](https://docs.microsoft.com/en-us/nimbusml/overview) 1.4.0 + +## **New Features** + +- **Add initial implementation of DatasetTransformer.** + + [PR#240](https://github.com/microsoft/NimbusML/pull/240) + This transform allows a fitted transformer based model to be inserted + in to another `Pipeline`. + + ```python + Pipeline([ + DatasetTransformer(transform_model=transform_pipeline.model), + OnlineGradientDescentRegressor(label='c2', feature=['c1']) + ]) + ``` + +## **Bug Fixes** + +- **Fixed `classes_` attribute when no `y` input specified ** + + [PR#218](https://github.com/microsoft/NimbusML/pull/218) + Fix a bug with the classes_ attribute when no y input is specified during fitting. + This addresses [issue 216](https://github.com/microsoft/NimbusML/issues/216) + +- **Fixed Add NumSharp.Core.dll ** + + [PR#220](https://github.com/microsoft/NimbusML/pull/220) + Fixed a bug that prevented running TensorFlowScorer. + This addresses [issue 219](https://github.com/microsoft/NimbusML/issues/219) + +- **Fixed Enable scoring of ML.NET models saved with new TransformerChain format ** + + [PR#230](https://github.com/microsoft/NimbusML/pull/230) + Fixed error loading a model that was saved with mlnet auto-train. + This addresses [issue 201](https://github.com/microsoft/NimbusML/issues/201) + +- **Fixed Pass python path to Dprep package ** + + [PR#232](https://github.com/microsoft/NimbusML/pull/232) + Enable passing python executable to dataprep package, so dataprep can execute python transformations + +## **Breaking Changes** + +None. + +## **Enhancements** + +None. + +## **Documentation and Samples** + +None. + +## **Remarks** + +None. diff --git a/release-next.md b/release-next.md index 8ad35e66..504e4763 100644 --- a/release-next.md +++ b/release-next.md @@ -2,52 +2,64 @@ ## **New Features** -- **Add initial implementation of DatasetTransformer.** +- **Initial implementation of `csr_matrix` output support.** - [PR#240](https://github.com/microsoft/NimbusML/pull/240) - This transform allows a fitted transformer based model to be inserted - in to another `Pipeline`. + [PR#250](https://github.com/microsoft/NimbusML/pull/250) + Add support for data output in `scipy.sparse.csr_matrix` format. ```python - Pipeline([ - DatasetTransformer(transform_model=transform_pipeline.model), - OnlineGradientDescentRegressor(label='c2', feature=['c1']) - ]) + xf = OneHotVectorizer(columns={'c0':'c0', 'c1':'c1'}) + xf.fit(train_df) + result = xf.transform(train_df, as_csr=True) ``` -## **Bug Fixes** +- **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.** -- **Fixed `classes_` attribute when no `y` input specified ** + [PR#267](https://github.com/microsoft/NimbusML/pull/267) + Support output of columns returned from ML.Net which contain variable length vectors. - [PR#218](https://github.com/microsoft/NimbusML/pull/218) - Fix a bug with the classes_ attribute when no y input is specified during fitting. - This addresses [issue 216](https://github.com/microsoft/NimbusML/issues/216) +- **Save `predictor_model` when pickling a `Pipeline`.** -- **Fixed Add NumSharp.Core.dll ** + [PR#295](https://github.com/microsoft/NimbusML/pull/295) - [PR#220](https://github.com/microsoft/NimbusML/pull/220) - Fixed a bug that prevented running TensorFlowScorer. - This addresses [issue 219](https://github.com/microsoft/NimbusML/issues/219) +- **Initial implementation of the WordTokenizer transform.** -- **Fixed Enable scoring of ML.NET models saved with new TransformerChain format ** + [PR#296](https://github.com/microsoft/NimbusML/pull/296) - [PR#230](https://github.com/microsoft/NimbusML/pull/230) - Fixed error loading a model that was saved with mlnet auto-train. - This addresses [issue 201](https://github.com/microsoft/NimbusML/issues/201) +- **Add support for summary output from tree based predictors.** -- **Fixed Pass python path to Dprep package ** + [PR#298](https://github.com/microsoft/NimbusML/pull/298) - [PR#232](https://github.com/microsoft/NimbusML/pull/232) - Enable passing python executable to dataprep package, so dataprep can execute python transformations +## **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 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`.