{"id":15063997,"url":"https://github.com/genfifth/cvopt","last_synced_at":"2025-04-10T11:50:45.841Z","repository":{"id":62566077,"uuid":"109551739","full_name":"genfifth/cvopt","owner":"genfifth","description":"Machine learning's parameter search and feature selection module which is  integrated log management and visualization.","archived":false,"fork":false,"pushed_at":"2020-01-04T03:29:33.000Z","size":2585,"stargazers_count":13,"open_issues_count":2,"forks_count":6,"subscribers_count":0,"default_branch":"master","last_synced_at":"2025-03-24T10:38:52.333Z","etag":null,"topics":["bayesian-optimization","deep-learning","feature-selection","hyperopt","hyperparameter-optimization","integrated-visualization","keras","logmanagement","machine-learning","python","scikit-learn"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-2-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/genfifth.png","metadata":{"files":{"readme":"README.md","changelog":"Changelog.md","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":"2017-11-05T04:29:25.000Z","updated_at":"2021-06-29T08:30:39.000Z","dependencies_parsed_at":"2022-11-03T18:51:39.397Z","dependency_job_id":null,"html_url":"https://github.com/genfifth/cvopt","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/genfifth%2Fcvopt","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/genfifth%2Fcvopt/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/genfifth%2Fcvopt/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/genfifth%2Fcvopt/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/genfifth","download_url":"https://codeload.github.com/genfifth/cvopt/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248102154,"owners_count":21048116,"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":["bayesian-optimization","deep-learning","feature-selection","hyperopt","hyperparameter-optimization","integrated-visualization","keras","logmanagement","machine-learning","python","scikit-learn"],"created_at":"2024-09-25T00:09:56.956Z","updated_at":"2025-04-10T11:50:45.823Z","avatar_url":"https://github.com/genfifth.png","language":"Python","readme":"# cvopt -to simplify Data Science-\ncvopt (cross validation optimizer) is python module for machine learning's parameter search and feature selection.\nTo simplify modeling, in cvopt, log management and visualization are integrated and the API like scikit-learn is provided.\n\n![readme_00](https://github.com/genfifth/cvopt/blob/master/etc/images/readme_00.PNG)\n\nIn Data Science modeling, sometimes would like to ...\n* Use various search algorithms on the same interface.\n* Optimize parameters and feature selections simultaneously.\n* Integrate log management and its visualization into search API.\n\nTo make these simpler, cvopt was created.\n\n# Features\n* API like scikit-learn.\n   * Support Algorithm:\n      * Sequential Model Based Global Optimization (Hyperopt)\n      * Bayesian Optimization (GpyOpt)\n      * Genetic Algorithm\n      * Random Search\n* Optimization of parameters and feature selections.\n* Integration of log management and visualization.\n\n\n# Installation   \n```bash\n$ pip install Gpy\n$ pip install cvopt\n```\nRequires:   \n* Python3\n* NumPy\n* pandas\n* scikit-learn\n* Hyperopt\n* Gpy\n* GpyOpt\n* bokeh\n   \n# Quick start -search can be written in 5 lines.-\n```python\nparam_distributions = {\"penalty\": search_category(['l1', 'l2']), \"C\": search_numeric(0, 3, \"float\"), \n                       \"tol\" : search_numeric(0, 4, \"float\"),  \"class_weight\" : search_category([None, \"balanced\"])}\nfeature_groups = np.random.randint(0, 5, Xtrain.shape[1]) \nopt = SimpleoptCV(estimator=LogisticRegression(), param_distributions=param_distributions)\nopt.fit(Xtrain, ytrain, feature_groups=feature_groups)\n```\n   \n# Documents\nBasic usage[(en)](https://github.com/genfifth/cvopt/blob/master/notebooks/basic_usage.ipynb)/[(jp)](https://github.com/genfifth/cvopt/blob/master/notebooks/basic_usage_jp.ipynb)\n   \n[Keras sample](https://github.com/genfifth/cvopt/blob/master/notebooks/keras_sample.ipynb)\n   \n[API Reference](https://genfifth.github.io/cvopt/)\n\n# Changelog\n[Log](https://github.com/genfifth/cvopt/blob/master/Changelog.md)   \n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgenfifth%2Fcvopt","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgenfifth%2Fcvopt","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgenfifth%2Fcvopt/lists"}