{"id":20040909,"url":"https://github.com/littlelittlecloud/auto-machinelearning","last_synced_at":"2025-07-23T15:39:55.103Z","repository":{"id":55672409,"uuid":"256358937","full_name":"LittleLittleCloud/auto-machinelearning","owner":"LittleLittleCloud","description":"Provides easy API to create and train sweepable pipeline for ML.Net over a group of pre-defined paramaters and trainers","archived":false,"fork":false,"pushed_at":"2022-12-08T10:30:20.000Z","size":2291,"stargazers_count":8,"open_issues_count":4,"forks_count":1,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-06-23T17:49:48.994Z","etag":null,"topics":["automated-machine-learning","automl","machine-learning","machinelearning-csharp","mlnet"],"latest_commit_sha":null,"homepage":"","language":"C#","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/LittleLittleCloud.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE.TXT","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2020-04-17T00:13:00.000Z","updated_at":"2025-01-25T01:54:28.000Z","dependencies_parsed_at":"2023-01-25T07:15:50.822Z","dependency_job_id":null,"html_url":"https://github.com/LittleLittleCloud/auto-machinelearning","commit_stats":null,"previous_names":["littlelittlecloud/machinelearning-auto-pipeline"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/LittleLittleCloud/auto-machinelearning","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LittleLittleCloud%2Fauto-machinelearning","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LittleLittleCloud%2Fauto-machinelearning/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LittleLittleCloud%2Fauto-machinelearning/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LittleLittleCloud%2Fauto-machinelearning/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/LittleLittleCloud","download_url":"https://codeload.github.com/LittleLittleCloud/auto-machinelearning/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LittleLittleCloud%2Fauto-machinelearning/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":266706612,"owners_count":23971904,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-07-23T02:00:09.312Z","response_time":66,"last_error":null,"robots_txt_status":null,"robots_txt_updated_at":null,"robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["automated-machine-learning","automl","machine-learning","machinelearning-csharp","mlnet"],"created_at":"2024-11-13T10:44:36.601Z","updated_at":"2025-07-23T15:39:55.084Z","avatar_url":"https://github.com/LittleLittleCloud.png","language":"C#","funding_links":[],"categories":[],"sub_categories":[],"readme":"## **MLNet.AutoPipeline**: AutoML for [ML.NET](https://dotnet.microsoft.com/apps/machinelearning-ai/ml-dotnet)\n\n**ML.Net AutoPipeline** is a set of packages build on top of ML.Net that provide AutoML feature. It is aimed to solve the two following problems that vastly exists in Machinelearning:\n- Given a ML pipeline, find the best hyper-parameters for its transformers or trainers.\n- Given a dataset and a ML task, find the best pipeline for solving this task.\n\n[![Build Status](https://dev.azure.com/xiaoyuz0315/BigMiao/_apis/build/status/LittleLittleCloud.auto-machinelearning?branchName=master)](https://dev.azure.com/xiaoyuz0315/BigMiao/_build/latest?definitionId=3\u0026branchName=master) ![Azure DevOps coverage](https://img.shields.io/azure-devops/coverage/xiaoyuz0315/BigMiao/3?color=green) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)\n\n## Try it on Binder\n[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/LittleLittleCloud/MLNet-AutoPipeline-Examples/master)\n\n## Quick Start\n\nFirst, add `MLNet.AutoPipeline` to your project. You can get those packages from our [nightly build](#Installation).\n\n```xml\n\u003cItemGroup\u003e\n  \u003cPackageReference Include=\"MLNet.AutoPipeline\" /\u003e\n\u003c/ItemGroup\u003e\n```\nThen create a `SweepablePipeline` using `AutoPipelineCatalog` API. `SweepablePipeline` is similar to the concept of [`EstimatorChain`](https://docs.microsoft.com/en-us/dotnet/api/microsoft.ml.data.estimatorchain-1?view=ml-dotnet) in ML.Net. And it will fine-tune hyperparameters by sweeping over a group of pre-defined parameters during training.\n\n```csharp\nvar context = new MLContext();\nvar sweepablePipeline = context.Transforms.Conversion.MapValueToKey(\"species\", \"species\")\n                    // here we use Iris dataset as example.\n                    .Append(context.Transforms.Concatenate(\"features\", new string[] { \"sepal_length\", \"sepal_width\", \"petal_length\", \"petal_width\" }))\n                    // create a sweepable LbfgsMaximumEntropy trainer\n                    .Append(context.AutoML().MultiClassification.LbfgsMaximumEntropy(\"species\", \"features\"));\n```\n\nThen create an `Experiment` to sweep over `sweepablePipeline` to find the best pipeline and hyperparameter.\n\n```csharp\nvar experimentOption = new Experiment.Option()\n{\n    EvaluateFunction = (MLContext context, IDataView data) =\u003e\n                {\n                    return context.MulticlassClassification.Evaluate(data, \"iris\").MicroAccuracy;\n                }, // Use Micro Accuracy as evaluate metric.\n};\n\nvar experiment = context.AutoML().CreateExperiment(estimatorChain, experimentOption)\nvar result = await experiment.TrainAsync(split.TrainSet); // train experiment.\n```\n\n## Examples\nPlease visit [MLNet-AutoPipeline-Example](https://github.com/LittleLittleCloud/MLNet-AutoPipeline-Examples) for MLNet.AutoPipeline examples.\n\n## Installation\n\nThis project is still under developing, so no released package is available yet. However, you can get the prereleased version below.\n\n|[auto-pipeline](https://dev.azure.com/xiaoyuz0315/BigMiao/_packaging?_a=feed\u0026feed=MLNet-Auto-Pipeline%40Prerelease)|Pre-released|\n|-|-|\n|MLNet.AutoPipeline|[![MLNet.AutoPipeline package in MLNet-Auto-Pipeline@Prerelease feed in Azure Artifacts](https://feeds.dev.azure.com/xiaoyuz0315/1bf31d68-811d-4872-ae8b-cdd289c934f1/_apis/public/Packaging/Feeds/360eccf9-f423-4798-85f2-57d25eecbd49%40c1004200-b0de-4d5b-8208-7464f565e1a8/Packages/f14318be-ef42-4f8a-8930-76a801345968/Badge)](https://dev.azure.com/xiaoyuz0315/BigMiao/_packaging?_a=package\u0026feed=360eccf9-f423-4798-85f2-57d25eecbd49%40c1004200-b0de-4d5b-8208-7464f565e1a8\u0026package=f14318be-ef42-4f8a-8930-76a801345968\u0026preferRelease=true)|\n|MLNet.Sweeper|[![MLNet.Sweeper package in MLNet-Auto-Pipeline@Prerelease feed in Azure Artifacts](https://feeds.dev.azure.com/xiaoyuz0315/1bf31d68-811d-4872-ae8b-cdd289c934f1/_apis/public/Packaging/Feeds/360eccf9-f423-4798-85f2-57d25eecbd49%40c1004200-b0de-4d5b-8208-7464f565e1a8/Packages/681d6c5b-20bd-4794-bbec-8fc8a54c6ea6/Badge)](https://dev.azure.com/xiaoyuz0315/BigMiao/_packaging?_a=package\u0026feed=360eccf9-f423-4798-85f2-57d25eecbd49%40c1004200-b0de-4d5b-8208-7464f565e1a8\u0026package=681d6c5b-20bd-4794-bbec-8fc8a54c6ea6\u0026preferRelease=true)|\n|MLNet.Expert|[![MLNet.Expert package in MLNet-Auto-Pipeline feed in Azure Artifacts](https://feeds.dev.azure.com/xiaoyuz0315/1bf31d68-811d-4872-ae8b-cdd289c934f1/_apis/public/Packaging/Feeds/360eccf9-f423-4798-85f2-57d25eecbd49/Packages/7c3ea9b1-81eb-4ea6-8c9f-35fcbd890f45/Badge)](https://dev.azure.com/xiaoyuz0315/BigMiao/_packaging?_a=package\u0026feed=360eccf9-f423-4798-85f2-57d25eecbd49\u0026package=7c3ea9b1-81eb-4ea6-8c9f-35fcbd890f45\u0026preferRelease=true)|\n\n## Contributing\nWe welcome contributions! Please see our [contribution guide](CONTRIBUTING.md)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flittlelittlecloud%2Fauto-machinelearning","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flittlelittlecloud%2Fauto-machinelearning","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flittlelittlecloud%2Fauto-machinelearning/lists"}