Microsoft.ML.LightGbm
4.0.2
Prefix Reserved
There is a newer prerelease version of this package available.
See the version list below for details.
See the version list below for details.
dotnet add package Microsoft.ML.LightGbm --version 4.0.2
NuGet\Install-Package Microsoft.ML.LightGbm -Version 4.0.2
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package.
<PackageReference Include="Microsoft.ML.LightGbm" Version="4.0.2" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
<PackageVersion Include="Microsoft.ML.LightGbm" Version="4.0.2" />
<PackageReference Include="Microsoft.ML.LightGbm" />
For projects that support Central Package Management (CPM), copy this XML node into the solution Directory.Packages.props file to version the package.
paket add Microsoft.ML.LightGbm --version 4.0.2
The NuGet Team does not provide support for this client. Please contact its maintainers for support.
#r "nuget: Microsoft.ML.LightGbm, 4.0.2"
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package.
#addin nuget:?package=Microsoft.ML.LightGbm&version=4.0.2
#tool nuget:?package=Microsoft.ML.LightGbm&version=4.0.2
The NuGet Team does not provide support for this client. Please contact its maintainers for support.
About
ML.NET is a cross-platform open-source machine learning framework which makes machine learning accessible to .NET developers.
For more information, see the ML.NET documentation.
This package adds the ability to use LightGBM based transformers, a gradient boosting framework that uses tree based learning algorithms.
Key Features
- Classification/Categorization - Automatically divide customer feedback into positive and negative categories
- Regression/Predict continuous values - Predict the price of houses based on size and location
- Recommendations - Suggest products that online shoppers may want to buy, based on their previous purchases
How to Use
See Machine Learning Samples for an assortment of samples that show how to get started using ML.NET.
Main Types
Some of the types provided by this library are:
Microsoft.ML.Trainers.LightGbm.GradientBoosterMicrosoft.ML.Trainers.LightGbm.DartBoosterMicrosoft.ML.Trainers.LightGbm.GossBoosterMicrosoft.ML.Trainers.LightGbm.LightGbmBinaryTrainer
Additional Documentation
Related Packages
- Main Package: Microsoft.ML
- Core data abstraction: Microsoft.ML.DataView
- Fast Tree: Microsoft.ML.FastTree
- Image analytics: Microsoft.ML.ImageAnalytics
- Recommender: Microsoft.ML.Recommender
- Time series: Microsoft.ML.TimeSeries
- Automatic model selection / tuning: Microsoft.ML.AutoML
- Exporting Onnx Models: Microsoft.ML.OnnxConverter
- Loading Onnx models: Microsoft.ML.OnnxTransformer
- Text tokenizers: Microsoft.ML.Tokenizers
Feedback & Contributing
Microsoft.ML is released as open source under the MIT license. Bug reports and contributions are welcome at the GitHub repository.
| Product | Versions Compatible and additional computed target framework versions. |
|---|---|
| .NET | net5.0 was computed. net5.0-windows was computed. net6.0 was computed. net6.0-android was computed. net6.0-ios was computed. net6.0-maccatalyst was computed. net6.0-macos was computed. net6.0-tvos was computed. net6.0-windows was computed. net7.0 was computed. net7.0-android was computed. net7.0-ios was computed. net7.0-maccatalyst was computed. net7.0-macos was computed. net7.0-tvos was computed. net7.0-windows was computed. net8.0 was computed. net8.0-android was computed. net8.0-browser was computed. net8.0-ios was computed. net8.0-maccatalyst was computed. net8.0-macos was computed. net8.0-tvos was computed. net8.0-windows was computed. net9.0 was computed. net9.0-android was computed. net9.0-browser was computed. net9.0-ios was computed. net9.0-maccatalyst was computed. net9.0-macos was computed. net9.0-tvos was computed. net9.0-windows was computed. |
| .NET Core | netcoreapp2.0 was computed. netcoreapp2.1 was computed. netcoreapp2.2 was computed. netcoreapp3.0 was computed. netcoreapp3.1 was computed. |
| .NET Standard | netstandard2.0 is compatible. netstandard2.1 was computed. |
| .NET Framework | net461 was computed. net462 was computed. net463 was computed. net47 was computed. net471 was computed. net472 was computed. net48 was computed. net481 was computed. |
| MonoAndroid | monoandroid was computed. |
| MonoMac | monomac was computed. |
| MonoTouch | monotouch was computed. |
| Tizen | tizen40 was computed. tizen60 was computed. |
| Xamarin.iOS | xamarinios was computed. |
| Xamarin.Mac | xamarinmac was computed. |
| Xamarin.TVOS | xamarintvos was computed. |
| Xamarin.WatchOS | xamarinwatchos was computed. |
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.
-
.NETStandard 2.0
- LightGBM (>= 3.3.5)
- Microsoft.ML (>= 4.0.2)
- Microsoft.ML.FastTree (>= 4.0.2)
NuGet packages (9)
Showing the top 5 NuGet packages that depend on Microsoft.ML.LightGbm:
| Package | Downloads |
|---|---|
|
Microsoft.ML.AutoML
ML.NET AutoML: Optimizes an ML pipeline for your dataset, by automatically locating the best feature engineering, model, and hyperparameters |
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dexih.functions.ml
Data transformation and Anaytics library - Machine Learning Functions |
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Microsoft.ProgramSynthesis.Transformation.Formula.MachineLearning
Supporting library for Machine Learning capabilities in the Transformation.Formula DSL. |
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ProteoformExplorer
Proteoform Dashboard for WPF Applications |
|
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Vintasoft.Imaging.Ocr.ML
Recognize line of handwritten digits in image using neural network. |
GitHub repositories (8)
Showing the top 8 popular GitHub repositories that depend on Microsoft.ML.LightGbm:
| Repository | Stars |
|---|---|
|
dotnet/machinelearning
ML.NET is an open source and cross-platform machine learning framework for .NET.
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CodeMazeBlog/CodeMazeGuides
The main repository for all the Code Maze guides
|
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zLulus/NotePractice
My_Note 笔记练习demo
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buraksenyurt/skynet
Some kinds of programming tutorials on MacOS/Windows/Linux. There are 41 sample applications.
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maker-community/ElectronBot.DotNet
一个为ElectronBot机器人和瀚文键盘（HelloWorldKeyboard）开发的上位机软件（包含机器人USB操作SDK和瀚文键盘HID操作SDK），采用Windows App SDK框架编写界面。 A host computer software developed for ElectronBot robots (including robot USB operation SDK), using the Windows App SDK framework to write UI.
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SoftUni/csharp-web
This is the official GitHub repository for the C# Web Development courses @ SoftUni
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changhuixu/dotnetlabs
.NET Labs -- Show Me the Tips and Tricks and Code
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jeffprosise/ML.NET
Code samples utilizing Microsoft's ML.NET machine-learning library
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| Version | Downloads | Last updated |
|---|---|---|
| 5.0.0-preview.1.25127.4 | 605 | 2/28/2025 |
| 5.0.0-preview.1.25125.4 | 141 | 2/25/2025 |
| 4.0.2 | 5,840 | 2/26/2025 |
| 4.0.1 | 10,591 | 1/15/2025 |
| 4.0.0 | 16,765 | 11/13/2024 |
| 4.0.0-preview.24522.7 | 319 | 10/23/2024 |
| 4.0.0-preview.24378.1 | 1,476 | 7/29/2024 |
| 4.0.0-preview.24271.1 | 1,346 | 5/21/2024 |
| 4.0.0-preview.24162.2 | 1,489 | 3/13/2024 |
| 3.0.1 | 142,002 | 1/18/2024 |
| 3.0.0 | 33,010 | 11/27/2023 |
| 3.0.0-preview.23511.1 | 813 | 10/13/2023 |
| 3.0.0-preview.23266.6 | 10,435 | 5/17/2023 |
| 3.0.0-preview.22621.2 | 2,443 | 12/22/2022 |
| 2.0.1 | 193,169 | 2/1/2023 |
| 2.0.1-preview.22573.9 | 1,467 | 11/24/2022 |
| 2.0.0 | 63,570 | 11/8/2022 |
| 2.0.0-preview.22551.1 | 1,144 | 11/1/2022 |
| 2.0.0-preview.22313.1 | 4,758 | 6/14/2022 |
| 1.7.1 | 736,569 | 3/9/2022 |
| 1.7.0 | 169,485 | 11/9/2021 |
| 1.7.0-preview.final | 488 | 10/22/2021 |
| 1.6.0 | 42,988 | 7/15/2021 |
| 1.5.5 | 2,881,946 | 3/4/2021 |
| 1.5.4 | 60,628 | 12/17/2020 |
| 1.5.2 | 55,346 | 9/11/2020 |
| 1.5.1 | 25,458 | 7/11/2020 |
| 1.5.0 | 29,147 | 5/26/2020 |
| 1.5.0-preview2 | 20,465 | 3/12/2020 |
| 1.5.0-preview | 23,027 | 12/26/2019 |
| 1.4.0 | 164,153 | 11/5/2019 |
| 1.4.0-preview2 | 4,074 | 10/8/2019 |
| 1.4.0-preview | 4,662 | 8/30/2019 |
| 1.3.1 | 30,005 | 8/6/2019 |
| 1.2.0 | 36,199 | 7/3/2019 |
| 1.1.0 | 10,109 | 6/4/2019 |
| 1.0.0 | 77,946 | 5/2/2019 |
| 1.0.0-preview | 80,911 | 4/2/2019 |
| 0.11.0 | 2,987 | 3/6/2019 |
| 0.10.0 | 2,153 | 2/5/2019 |
| 0.9.0 | 9,511 | 1/8/2019 |
| 0.8.0 | 2,073 | 12/4/2018 |
| 0.7.0 | 2,047 | 11/6/2018 |
| 0.6.0 | 4,876 | 10/2/2018 |
| 0.5.0 | 1,967 | 9/5/2018 |
| 0.4.0 | 1,902 | 8/7/2018 |
| 0.3.0 | 55,362 | 7/3/2018 |