infer
Infer.NET is a framework for running Bayesian inference in graphical models. It can also be used for probabilistic programming.
One can use Infer.NET to solve many different kinds of machine learning problems - from standard problems like classification,recommendation or clustering through to customised solutions to domain-specific problems.
Infer.NET has been used in a wide variety of domains including information retrieval, bioinformatics, epidemiology, vision, and many others.
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Binaries for Infer.NET are located on nuget.org. These binaries are cross-platform and work anywhere that .NET is supported, so there is no need to select your platform. The core packages target .NET Standard 2.0, making them useable from any project that targets .NET framework version 4.6.1 or .NET Core 2.1, as explained at .NET implementation support. You do not need to clone the GitHub repository to use the pre-built binaries.
There currently are four maintained Infer.NET nuget packages:
Microsoft.ML.Probabilistic
contains classes and methods needed to execute the inference code.
Microsoft.ML.Probabilistic.Compiler
contains the
Infer.NET Compiler, which takes model descriptions written using the
Infer.NET API and converts them into inference code. It also contains
utilities for the visualization of the generated code.
Microsoft.ML.Probabilistic.Learners
contains complete machine learning applications including a classifier and a recommender system.
Microsoft.ML.Probabilistic.Visualizers.Windows
contains an alternative .NET Framework and Windows specific set of visualization tools for exploring and analyzing models.
NuGet packages do not need to be manually downloaded. Instead, you
add the package name to your project file, and the binaries are
downloaded automatically when the project is compiled. Most code
editors have an option to add a NuGet package reference to an existing
project file. For example, in Visual Studio 2017 for Windows, you select Project -> Manage NuGet packages
.
.NET Core 2.1 provides command-line tools for creating and editing project files. Using the command line, you can add a NuGet package reference to an existing project file with:
dotnet add package Microsoft.ML.Probabilistic dotnet add package Microsoft.ML.Probabilistic.Compiler dotnet add package Microsoft.ML.Probabilistic.Learners
There is a getting started guide on docs.microsoft.com.
More tutorials and examples can be found on the Infer.NET website.
Documentation can be found on the Infer.NET website.
The Visual Studio solution Infer.sln
in the root of the
repository contains all Infer.NET components, unit tests and sample
programs from the folders described below.
src/
ClickThroughModel
- a web search example of converting a sequence of clicks by the user into inferences about the relevance of documents.
ClinicalTrial
- the clinical trial tutorial example with an interactive user interface.
InferNET101
- samples from Infer.NET 101 introduction to the basics of Microsoft Infer.NET programming.
ImageClassifier
- an image search example of classifying tagged images.
LDA
- this example provides Infer.NET implementations of
the popular LDA model for topic modeling. The implementations pay
special attention to scalability with respect to vocabulary size, and
with respect to the number of documents. As such, they provide good
examples for how to scale Infer.NET models in general.
MontyHall
- an Infer.NET implementation of the Monty Hall problem, along with a graphical user interface.
MotifFinder
- an Infer.NET implementation of a simple
model for finding motifs in nucleotide sequences, which constitutes an
important problem in bioinformatics.
Compiler
contains the Infer.NET Compiler project which
takes model descriptions written using the Infer.NET API, and converts
them into inference code. The project also contains utility methods for
visualization of the generated code.
Csoft
is an experimental feature that allows to express
probabilistic models in a subset of the C# language. You can find many
unit tests of Csoft
models in the Tests
project marked with Category: CsoftModel
trait.
Examples
contains C# projects that illustrate how to use Infer.NET to solve a variety of different problems.
FSharpWrapper
is a wrapper project that hides some of
the generic constructs in the Infer.NET API allowing simpler calls to
the Infer.NET API from standard F#.
IronPythonWrapper
contains wrapper for calling Infer.NET from the IronPython programming language and tests for the wrapper. Please refer to README.md for more information.
Learners
folder contains Visual Studio projects for
complete machine learning applications including classification and
recommendation. You can read more about Learners here.
Runtime
- is a C# project with classes and methods needed to execute the inference code.
Tutorials
contains Examples Browser project with simple examples that provide a step-by-step introduction to Infer.NET.
Visualizers/Windows
contains an alternative .NET
Framework and Windows specific set of visualization tools for exploring
and analyzing the code generated by the Compiler
.
test/
TestApp
contains C# console application for quick invocation and debugging of various Infer.NET components.
TestFSharp
is an F# console project for smoke testing of Infer.NET F# wrapper.
TestPublic
contains scenario tests for tutorial code. These tests are a part of the PR and nightly builds.
Tests
- main unit test project containing thousands of tests. These tests are a part of the PR and nightly builds. The folder TestsVibes
contains MATLab scripts that compare Infer.NET to the VIBES package. Running them requires Vibes2_0.jar
(can be obtained on the VIBES website) to be present in the same folder.
Learners
folder contains the unit tests and the test application for Learners
(see above).
build
folder contains the YAML definitions for the Continuous Integration builds and the specification files for the nuget packages.
docs
folder contains the scripts for building API documentation and for updating https://dotnet.github.io/infer. Please refer to README.md for more details.
Please, refer to our building guide.
We welcome contributions! Please review our contribution guide.
When submitting pull request with changed or added factor, please make sure you updated factor documentation as described here.
Infer.NET is licensed under the MIT license.
Infer.NET is a .NET Foundation project. It's also a part of ML.NET machine learning framework.
There are many .NET related projects on GitHub.
.NET home repo - links to 100s of .NET projects, from Microsoft and the community.
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