{"id":15910906,"url":"https://github.com/radlfabs/flexcv-earth","last_synced_at":"2025-07-12T15:13:53.456Z","repository":{"id":207410467,"uuid":"719181644","full_name":"radlfabs/flexcv-earth","owner":"radlfabs","description":"Python Wrapper Class for R::Earth Regression Splines using rpy2","archived":false,"fork":false,"pushed_at":"2023-11-16T18:08:24.000Z","size":1014,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-03T01:42:21.609Z","etag":null,"topics":["machine-learning-algorithms","prediciton","regression"],"latest_commit_sha":null,"homepage":"https://radlfabs.github.io/flexcv-earth/","language":"Python","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/radlfabs.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,"governance":null,"roadmap":null,"authors":null}},"created_at":"2023-11-15T16:16:43.000Z","updated_at":"2023-11-16T17:51:00.000Z","dependencies_parsed_at":"2023-11-15T17:37:52.444Z","dependency_job_id":"3f7475d2-d452-4e4c-87e0-ead6f786e82e","html_url":"https://github.com/radlfabs/flexcv-earth","commit_stats":{"total_commits":19,"total_committers":2,"mean_commits":9.5,"dds":0.368421052631579,"last_synced_commit":"978722cd07eb8b3ec3c5ef21b7bdfe605dac86c4"},"previous_names":["radlfabs/flexcv-earth"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/radlfabs/flexcv-earth","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/radlfabs%2Fflexcv-earth","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/radlfabs%2Fflexcv-earth/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/radlfabs%2Fflexcv-earth/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/radlfabs%2Fflexcv-earth/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/radlfabs","download_url":"https://codeload.github.com/radlfabs/flexcv-earth/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/radlfabs%2Fflexcv-earth/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":265009351,"owners_count":23697158,"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":["machine-learning-algorithms","prediciton","regression"],"created_at":"2024-10-06T15:22:22.332Z","updated_at":"2025-07-12T15:13:53.399Z","avatar_url":"https://github.com/radlfabs.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# flexcv-earth\n\nThis is a additional package for the python package [flexcv](https://github.com/radlfabs/flecv).\n`flexcv-earth` provides a wrapper class to use Earth model regression in python without the need to install `pyearth`.\nInstead, `flexcv-earth` uses the `rpy2` package to call the `earth` function from the `earth` package in R.\n\n## Installation\nMake sure to have Python 3.10 or 3.11 installed. Also, you will need to install R\n```\npip install flexcv_earth @ git+https://github.com/radlfabs/flexcv-earth\n```\n\n#### Additional dependencies of `rpy2`\n\nThe model class for the `EarthRegressor` is actually wrapping around `rpy2` code and is using embedded `R` under the hood. \nTherefore, you should have a recent `R` version installed and run our `install_rpackages.py` script. \nFrom the command line change your directory to your `flexcv-earth` installation directory. \nThis can be your folder that you created with `venv`. Run our python script that installs the remaining R dependencies.\n\n```bash\ncd path/to/flexcv-earth/\npython -m install_rpackages\n```\n\nNow you have installed everything you need to use the `EarthRegressor`with flexcv-earth.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fradlfabs%2Fflexcv-earth","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fradlfabs%2Fflexcv-earth","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fradlfabs%2Fflexcv-earth/lists"}