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Update release notes. (microsoft#306)
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57 changes: 57 additions & 0 deletions docs/release-notes/release-1.4.0.md
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# [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.
60 changes: 36 additions & 24 deletions release-next.md
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## **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`.

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