{"id":28429588,"url":"https://github.com/sktime/mlaut","last_synced_at":"2025-07-04T18:30:27.514Z","repository":{"id":57442234,"uuid":"112323127","full_name":"sktime/mlaut","owner":"sktime","description":null,"archived":false,"fork":false,"pushed_at":"2020-04-20T08:58:21.000Z","size":13204,"stargazers_count":24,"open_issues_count":7,"forks_count":5,"subscribers_count":6,"default_branch":"master","last_synced_at":"2025-06-30T00:26:43.756Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/sktime.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2017-11-28T10:50:28.000Z","updated_at":"2024-02-04T20:23:27.000Z","dependencies_parsed_at":"2022-09-26T17:21:08.255Z","dependency_job_id":null,"html_url":"https://github.com/sktime/mlaut","commit_stats":null,"previous_names":["alan-turing-institute/mlaut"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/sktime/mlaut","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sktime%2Fmlaut","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sktime%2Fmlaut/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sktime%2Fmlaut/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sktime%2Fmlaut/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sktime","download_url":"https://codeload.github.com/sktime/mlaut/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sktime%2Fmlaut/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":263499877,"owners_count":23476086,"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","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":[],"created_at":"2025-06-05T13:38:28.978Z","updated_at":"2025-07-04T18:30:27.508Z","avatar_url":"https://github.com/sktime.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cp align=\"center\"\u003e\n  \u003cimg src=\"/docs/_images/logo.png\" alt=\"mlaut\" width=\"300px\"\u003e\n\u003c/p\u003e\n\u003cp align=\"center\"\u003e\n  \u003ca href=\"https://badge.fury.io/py/mlaut\"\u003e\u003cimg src=\"https://badge.fury.io/py/mlaut.svg\" alt=\"PyPI version\" height=\"18\"\u003e\u003c/a\u003e\n  \u003ca href=\"https://opensource.org/licenses/BSD-3-Clause\"\u003e\u003cimg src=\"https://img.shields.io/badge/License-BSD%203--Clause-blue.svg\" alt=\"License\"\u003e\u003c/a\u003e\n\u003c/p\u003e\n\n\n# mlaut (Machine Learning AUtomation Toolbox)\n\n``mlaut`` is a modelling and workflow toolbox in python, written with the aim of simplifying large scale benchmarking of machine learning strategies, e.g., validation, evaluation and comparison with respect to predictive/task-specific performance or runtime. Key features are:\n\n* Automation of the most common workflows for benchmarking modelling strategies on multiple datasets including statistical post-hoc analyses, with user-friendly default settings.\n\n* Unified interface with support for scikit-learn strategies, keras deep neural network architectures, including easy user extensibility to (partially or completely) custom strategies.\n\n* Higher-level meta-data interface for strategies, allowing easy specification of scikit-learn pipelines and keras deep network architectures, with user-friendly (sensible) default configurations.\n\n* Easy setting up and loading of data set collections for local use (e.g., data frames from local memory, UCI repository, openML, Delgado study, PMLB).\n\n* Back-end agnostic, automated local file system management of datasets, fitted models, predictions, and results, with the ability to easily resume crashed benchmark experiments with long running times.\n\nList of [developers and contributors](AUTHORS.rst)\n\n### Documentation\n\n[\u003c\u003c\u003c\u003c\u003c\u003c Documentation available on alan-turing-institute.github.io/mlaut \u003e\u003e\u003e\u003e\u003e\u003e](https://alan-turing-institute.github.io/mlaut)\n\nAn example with the basic usage of ``mlaut`` can be found in the following [Jupyter Notebook](https://github.com/alan-turing-institute/mlaut/blob/master/examples/Benchmarking.ipynb)\n\n### Installing\n\nRequires Python 3.6 or greater.\n\n```\npip install mlaut\n```\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsktime%2Fmlaut","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsktime%2Fmlaut","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsktime%2Fmlaut/lists"}