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Release notes for v1.5.0-preview2 #4787
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- Additional changes to ExpressionTransformer ([#4614](https://github.com/dotnet/machinelearning/pull/4614)) | ||
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## **Test updates** | ||
- **Code analysis updates** |
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We don't ship code analyzer to our nuget users, why is this relevant to release notes?
CC: @eerhardt
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## **Test updates** | ||
- **Code analysis updates** | ||
- Update analyzer test library ([#4740](https://github.com/dotnet/machinelearning/pull/4740)) |
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We don't ship to users either.
## **Test updates** | ||
- **Code analysis updates** | ||
- Update analyzer test library ([#4740](https://github.com/dotnet/machinelearning/pull/4740)) | ||
- Enable the internal code analyzer for test projects ([#4731](https://github.com/dotnet/machinelearning/pull/4731)) |
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This is not shipped to the nuget users.
- **Better logging from tests** | ||
- Ensure tests capture the full log ([#4710](https://github.com/dotnet/machinelearning/pull/4710)) | ||
- Fix failure to capture test failures ([#4716](https://github.com/dotnet/machinelearning/pull/4716)) | ||
- Collect crash dump upload dump and pdb to artifact ([#4666](https://github.com/dotnet/machinelearning/pull/4666)) |
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How is collect crash dump relevant to nuget users? It will almost make them feel their data is being collected.
- Ensure tests capture the full log ([#4710](https://github.com/dotnet/machinelearning/pull/4710)) | ||
- Fix failure to capture test failures ([#4716](https://github.com/dotnet/machinelearning/pull/4716)) | ||
- Collect crash dump upload dump and pdb to artifact ([#4666](https://github.com/dotnet/machinelearning/pull/4666)) | ||
- Enable Conditional Numerical Reproducibility for tests ([#4569](https://github.com/dotnet/machinelearning/pull/4569)) |
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This is specific to test projects, we don't ship test projects.
- Implement MSML_ExtendBaseTestClass (Test classes should be derived from BaseTestClass) ([#4746](https://github.com/dotnet/machinelearning/pull/4746)) | ||
- Enable MSML_TypeParamName for the full solution ([#4762](https://github.com/dotnet/machinelearning/pull/4762)) | ||
- **Better logging from tests** | ||
- Ensure tests capture the full log ([#4710](https://github.com/dotnet/machinelearning/pull/4710)) |
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We don't ship tests.
- Added in support for System.DateTime type for the DateTimeTransformer ([#4661](https://github.com/dotnet/machinelearning/pull/4661)) | ||
- Additional changes to ExpressionTransformer ([#4614](https://github.com/dotnet/machinelearning/pull/4614)) | ||
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## **Test updates** |
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This whole section is not shipped to the users, why is this included in release notes? Who is your target audience and why would they care about stuff that is not shipped part of nuget?
- Other typo fixes:([#4628](https://github.com/dotnet/machinelearning/pull/4628), [#4685](https://github.com/dotnet/machinelearning/pull/4685)) | ||
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## **CLI and AutoML API** | ||
- CodeGen For AzureAttach ([#4498](https://github.com/dotnet/machinelearning/pull/4498)) |
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We don't want user aware of this change because this is only for ModelBuilder Azure Attach story
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- TextLoader, BinaryLoader and SvmLightLoader now check the existence of the input file before training ([#4665](https://github.com/dotnet/machinelearning/pull/4665)) | ||
- Changed onnx export to append a .onnx string to column names to support better mapping to ML.NET output column names ([#4734](https://github.com/dotnet/machinelearning/pull/4734)) | ||
- TextLoader, BinaryLoader and SvmLightLoader now check the existence of the input file before training ([#4665](https://github.com/dotnet/machinelearning/pull/4665)) | ||
- ImageClassificationTrainer now checks the existence of input folder before training ([#4691]( https://github.com/dotnet/machinelearning/pull/4691)) |
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this is ImagLoading transform not ImageClassification trainer, two very different things, one is a transformer and other is a trainer. #Resolved
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## **New Features (IN-PREVIEW, please provide feedback)** | ||
- **TimeSeriesImputer** ([#4623](https://github.com/dotnet/machinelearning/pull/4623)) | ||
- **LDSVM Trainer** ([#4060](https://github.com/dotnet/machinelearning/pull/4060)) |
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LDSVM Traine [](start = 4, length = 12)
Describe what this trainer is and where it is used and then provide links to samples. #Resolved
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Description:
LDSVM uses trees as its SVM kernel to create a non-linear binary learner.
Reference links:
http://manikvarma.org/pubs/jose13.pdf
http://manikvarma.org/talks/ICML13.pdf
#Resolved
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thanks and in addition I would also
expand LDSVM acronym. #Resolved
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"Local Deep SVM" #Resolved
# [ML.NET](http://dot.net/ml) 1.5.0-preview2 | ||
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## **New Features (IN-PREVIEW, please provide feedback)** | ||
- **TimeSeriesImputer** ([#4623](https://github.com/dotnet/machinelearning/pull/4623)) |
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TimeSeriesImputer [](start = 4, length = 17)
Describe what this transformer is and where it is used and then provide links to samples. #Resolved
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## **Bug Fixes** | ||
- Fix for OneVersusAllTrainer([#4698](https://github.com/dotnet/machinelearning/pull/4698)) |
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Space:
- Fix for OneVersusAllTrainer([#4698](https://github.com/dotnet/machinelearning/pull/4698)) | |
- Fix for OneVersusAllTrainer ([#4698](https://github.com/dotnet/machinelearning/pull/4698)) | |
``` #Resolved |
- Fix documentation of SvmLightLoader ([#4616](https://github.com/dotnet/machinelearning/pull/4616)) | ||
- Correct KMeans scoring function doc ([#4705](https://github.com/dotnet/machinelearning/pull/4705)) | ||
- Several typo fixes thanks to [@MaherJendoubi](https://github.com/MaherJendoubi) ([#4627](https://github.com/dotnet/machinelearning/pull/4627), [#4631](https://github.com/dotnet/machinelearning/pull/4631), [#4626](https://github.com/dotnet/machinelearning/pull/4626) [#4617](https://github.com/dotnet/machinelearning/pull/4617), [#4633](https://github.com/dotnet/machinelearning/pull/4633), [#4629](https://github.com/dotnet/machinelearning/pull/4629), [#4642](https://github.com/dotnet/machinelearning/pull/4642)) | ||
- Other typo fixes:([#4628](https://github.com/dotnet/machinelearning/pull/4628), [#4685](https://github.com/dotnet/machinelearning/pull/4685)) |
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Space:
- Other typo fixes:([#4628](https://github.com/dotnet/machinelearning/pull/4628), [#4685](https://github.com/dotnet/machinelearning/pull/4685)) | |
- Other typo fixes: ([#4628](https://github.com/dotnet/machinelearning/pull/4628), [#4685](https://github.com/dotnet/machinelearning/pull/4685)) | |
``` #Resolved |
- Changed onnx export to append a .onnx string to column names to support better mapping to ML.NET output column names ([#4734](https://github.com/dotnet/machinelearning/pull/4734)) | ||
- TextLoader, BinaryLoader and SvmLightLoader now check the existence of the input file before training ([#4665](https://github.com/dotnet/machinelearning/pull/4665)) | ||
- ImageLoadingTransformer now checks the existence of input folder before training ([#4691]( https://github.com/dotnet/machinelearning/pull/4691)) | ||
- Sweep Trimming of Whitespace in AutoML ([#3918](https://github.com/dotnet/machinelearning/pull/3918)) |
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This isn't in master; only in the AutoML branch. After testing it should be cherry picked to master. No need to mention here. #Resolved
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## **New Features (IN-PREVIEW, please provide feedback)** | ||
- **TimeSeriesImputer** ([#4623](https://github.com/dotnet/machinelearning/pull/4623)) This data transformer can be used to impute missing rows in time series data. | ||
- **LDSVM Trainer** ([#4060](https://github.com/dotnet/machinelearning/pull/4060)) The "Local Deep SVM" usess trees as its SVM kernel to create a non-linear binary trainer. A sample can be found [here](https://github.com/dotnet/machinelearning/blob/c819d77e9250c68883713d5f1cd79b8971a11faf/docs/samples/Microsoft.ML.Samples/Dynamic/Trainers/BinaryClassification/LdSvm.cs). |
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'usess' -> 'uses'
# [ML.NET](http://dot.net/ml) 1.5.0-preview2 | ||
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## **New Features (IN-PREVIEW, please provide feedback)** | ||
- **TimeSeriesImputer** ([#4623](https://github.com/dotnet/machinelearning/pull/4623)) This data transformer can be used to impute missing rows in time series data. |
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Should we add the nuget package here? i.e. which package the user has to install to get access to the component
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