machinelearning
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dotnet
ML.NET is an open source and cross-platform machine learning framework for .NET.
I am using ML.NET in C# to extract features for a reverse image search. It is based on the code sample from Microsoft's documentation at the following page: [https://learn.microsoft.com/en-us/dotnet/api/microsoft.ml.onnxcatalog.dnnfeaturizeimage?view=ml-dotnet#microsoft-ml-onnxcatalog-dnnfeaturizeimage(microsoft-ml-transformscatalog-system-string-system-func((microsoft-ml-transforms-onnx-dnnimagefeaturizerinput-microsoft-ml-data-estimatorchain((microsoft-ml-transforms-columncopyingtransformer))))-system-string)](url) I...
The example is for the `PermutationFeatureImportance`, not `PermutationFeatureImportanceNonCalibrated`. It looks like the example and remarks are copied over from: https://learn.microsoft.com/en-us/dotnet/api/microsoft.ml.permutationfeatureimportanceextensions.permutationfeatureimportance?view=ml-dotnet --- #### Document Details ⚠ *Do not edit this section....
The links to the Wikipedia page on N-grams and the L-p vector normalization are not being interpreted correctly on the TextFeaturizingEstimator page: ```markdown This estimator gives the user one-stop solution...
**System Information (please complete the following information):** - OS & Version: Windows 11 - ML.NET Version: - .NET Version: .NET 7 **Describe the bug** When loading a LightGBM model for...
**System Information:** - OS & Version: Windows 11 - ML.NET Version: ML.Net 2.0.1 - .NET Version: .NET 7.0 **Describe the bug** `PredictionEngine.Dispose()` does not dispose of all resources, leaving hundreds...
## What's few-shot/zero-shot HPO Few-shot HPO is a both promising-performance and budget-friendly HPO solution. It is divided into two processes: offline processing and online processing. In offline processing, it searches...
**Describe the solution you'd like** An extension `Summary()` method for `ITransformer` that returns a string that contains information like the hyper-parameter/Transformer name if `ITransformer` is a single Transformer, and returns...
When sending a `pipeline` containing `DropColumns` to a string type column to Execute of AutoML experiment as the `preFeaturizer` there is an exception `ArgumentOutOfRangeException: Could not find input column 'StringColumn'...
Expose cosine similarity, softmax, and other math utilities publicly. https://github.com/dotnet/machinelearning/blob/510f0112d4fbb4d3ee233b9ca95c83fae1f9da91/src/Microsoft.ML.Core/Utilities/MathUtils.cs#L735
Currently InferColumns only supports file data sources. Add SQL support to `InferColumns` so it can be used with DatabaseLoader.