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Native featurizers for AutoML (#317)
* Draft, adding CategoryImputer, ToKeyImputer, ToString transformers * add tests * prelim commit * update manifest, fix unit tests/examples * upgrade version * fix tests * temp hack fix for native libs * copy libFeaturizers.so * fix version * fix cp * fix version * Update ML.Net version number. * Update the examples and unit tests. * Update to latest version of the Featurizers library. * Fix test_tostring unit test. * Temporarily skip the estimator checks unit tests. * Upgrade pip to the latest version when installing the Python packages on Windows. This fixes an issue I had where scikit-learn would not install when building NimbusML with the RlsWinPy3.6 configuration because it could not find one of the test data sets. * Update test_estimator_checks for the three new transformers. * Remove extra comma from test_estimator_checks. * Update the ML.Net version. * Add TimeSeriesImputer * Add country param to DateTimeSplitter * Upgrade TensorFlow.NET version. Required by latest version of Microsoft.ML.Dnn. * Update ML.Net version and import new AutoMLFeaturizers package. * Add back in the accidentally removed tests from test_data_with_missing.py. * Update the DateTimeSplitter examples. * Update the ToKeyImputer examples. * Update the ToString examples. * Update build to support latest nuget packages and updates. * Remove copy of libFeaturizers from linux build script. * Add TimeSeriesImputer to the NimbusML project. * Add initial DataFrame based example for TimeSeriesImputer. * Update to the latest version of manifest.json. * Add missing project include for the TimeSeriesImputer example. * Update the DateTimeSplitter examples. * Update build files to copy over the Data folder which is required for the country support in the DateTimeSplitter transform. * Add a unit test for testing the holiday name return value for DateTimeSplitter. * Add unit test for ToKeyImputer. * Update to latest version of manifest.json. Makes grain input required for TimeSeriesImputer. * Update TimeSeriesImputer_df example. * Remove TimeSeriesImputer from test_estimator_checks. * Update nuget.config to point to relative directory for ml.net packages. * Add unit test for TimeSeriesImputer. * Use environmental variable to specify the local ml.net nuget package directory. * Update to the latest version of ml.net. * Add latest version of nuget packages for building. * Update to the latest windows ml.net binaries. * Add linux ml.net binaries. * adding correct nuget packages/location * adding correct ML.NET signed packages * adding correct ML.NET signed packages * Update the referenced ML.Net versions. * Update to the latest version of the manifest. * Add RobustScaler to the public API. * Fix spacing bug in RobustScalar in manifest.json. * Update to the latest version of manifest.json which contains naming fix for RobustScaler. * Update to latest unsigned nuget packages for testing RobustScaler and latest master features. * Add RobustScaler unit tests and examples. * Update to the latest signed ML.Net nugets. * Fix RobustScaler checks in test_estimator_checks. * up version
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