{"id":15288132,"url":"https://github.com/pysiakk/genetictree","last_synced_at":"2025-04-13T06:32:09.107Z","repository":{"id":54975732,"uuid":"288522036","full_name":"pysiakk/GeneticTree","owner":"pysiakk","description":"Constructing decision trees with genetic algorithm with a scikit-learn inspired API","archived":false,"fork":false,"pushed_at":"2021-07-31T13:53:41.000Z","size":800,"stargazers_count":24,"open_issues_count":6,"forks_count":3,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-04-11T12:14:48.381Z","etag":null,"topics":["classification","data-science","evolutionary-algorithm","genetic","genetic-algorithm","genetic-programming","genetictree","machine-learning","python","python-library","scikit-learn","tree"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/pysiakk.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2020-08-18T17:35:28.000Z","updated_at":"2023-10-12T21:49:29.000Z","dependencies_parsed_at":"2022-08-14T08:00:18.237Z","dependency_job_id":null,"html_url":"https://github.com/pysiakk/GeneticTree","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pysiakk%2FGeneticTree","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pysiakk%2FGeneticTree/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pysiakk%2FGeneticTree/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pysiakk%2FGeneticTree/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/pysiakk","download_url":"https://codeload.github.com/pysiakk/GeneticTree/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248674659,"owners_count":21143760,"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":["classification","data-science","evolutionary-algorithm","genetic","genetic-algorithm","genetic-programming","genetictree","machine-learning","python","python-library","scikit-learn","tree"],"created_at":"2024-09-30T15:44:16.519Z","updated_at":"2025-04-13T06:32:08.637Z","avatar_url":"https://github.com/pysiakk.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"[![forthebadge made-with-python](http://ForTheBadge.com/images/badges/made-with-python.svg)](https://www.python.org/)\n\n[![example workflow name](https://github.com/pysiakk/GeneticTree/workflows/GeneticTree/badge.svg)](https://github.com/pysiakk/GeneticTree/actions?query=workflow%3AGeneticTree)\n![codecov.io](https://codecov.io/github/pysiakk/GeneticTree/coverage.svg?branch=master)\n[![travis status](https://www.travis-ci.com/pysiakk/GeneticTree.svg?branch=master\u0026status=failed)](https://www.travis-ci.com/github/pysiakk/GeneticTree)\n\n# Genetic Tree\n\nThe main objective of the package is to allow creating decision trees that are better in some aspects than trees made by greedy algorithms.\n\nThe creation of trees is made by genetic algorithm.\nIn order to achive as fast as possible evolution of trees the most time consuming components are wrtitten in Cython.\nAlso there are implemented mechanisms for using old trees to create new ones without need to classify all observations from beggining (currently in developmnet).\nThere is planned to allow multithreading evolution.\n\nThe created trees should have smaller sizes with comparable accuracy to the trees made by greedy algorithms.\n\nProject is currently in development (before first version).\nThe first working official version should be developed in the January 2021 (with documentation and installation by pip).\n\n# Installation\n\nTo download the latest official release of the package use a pip command below:\n```bash\npip install genetic-tree\n```\n\n# Usage\n\nExample usage:\n```python\nfrom genetic_tree import GeneticTree\nfrom sklearn import datasets\n\niris = datasets.load_iris()       # get iris data\n\ngt = GeneticTree()\ngt.fit(iris.data, iris.target)\ny_pred = gt.predict(iris.data)    # it is recommended to predict on another subset of data than training\n```\nThe `y_pred` contains an array with classes predicted by the `GeneticTree`\n\n## License\n\nThe work is a bachelor thesis on Warsaw University of Technology.\n\nHigh-level interface of package is inspired by sklearn (https://github.com/scikit-learn/scikit-learn).\nEspecially there are methods like: fit(), predict(), predict_proba(), apply(), set_params(), check_X(), check_input() which are inspired and / or copied from sklearn.\n\nA low-level interface is inspired by sklearn decision_tree. The structure of tree (tree/tree.pyx) and some utils (tree/\\_utils.pyx) were copied from sklearn tree (https://github.com/scikit-learn/scikit-learn/tree/master/sklearn/tree).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpysiakk%2Fgenetictree","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpysiakk%2Fgenetictree","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpysiakk%2Fgenetictree/lists"}