{"adoption": {"forks": 763, "observed_at": "2026-08-28T04:06:28.960015+00:00", "stars": 2228}, "canonical_url": "https://ross.abutalabs.com/products/feature-selector", "card": {"archived": false, "artifact_type": "library", "description": "Feature selector is a tool for dimensionality reduction of machine learning datasets", "domain": ["machine-learning", "data-science"], "enriched": true, "function": ["machine-learning", "data-science", "data-visualization"], "health_score": 20, "homepage": null, "language": "Jupyter Notebook", "license": "GPL-3.0", "license_family": "copyleft", "maturity": "maintenance", "member_repos": ["WillKoehrsen/feature-selector"], "name": "WillKoehrsen/feature-selector", "platform": ["python"], "pushed_at": "2024-06-17T22:44:11+00:00", "repo": "WillKoehrsen/feature-selector", "stars": 2228, "tags": ["feature-selection", "dimensionality-reduction", "jupyter-notebook", "lightgbm", "pandas"], "topics": [], "urls": [], "use_cases": ["remove collinear features from a dataset", "drop features with too many missing values", "identify zero importance features before training", "reduce dimensionality of a machine learning dataset", "visualize feature correlations in a dataframe", "prune low importance features to speed up model training"], "what_it_is": "A Python library for feature selection that identifies features to remove from machine learning datasets using five methods: missing values, single unique values, collinear features, zero importance features, and low importance features. It includes visualization tools such as correlation heatmaps and feature importance plots.", "when_to_avoid": ["you need feature selection for non-tabular data like text or images", "you require actively maintained tooling with modern dependency versions", "you need scalable feature selection for very large datasets beyond memory"], "when_to_choose": ["you want a simple, notebook-friendly feature selection workflow for tabular data", "you need to inspect and visualize feature importance and collinearity before modeling", "you work with pandas DataFrames and want automated removal of redundant columns"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/feature-selector", "repo": "WillKoehrsen/feature-selector", "role": "main", "score": 32}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:06:28.960015+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-30T02:44:41.969440+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "05b075d505926efdd78162a08029c2a4fa807706b30cc5fbdeb43ba7c43d4143", "fetched_at": "2026-08-28T04:06:28.960015+00:00", "kind": "readme", "missing": false, "url": "https://github.com/WillKoehrsen/feature-selector"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:06:28.960015+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-30T02:44:41.969440+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "05b075d505926efdd78162a08029c2a4fa807706b30cc5fbdeb43ba7c43d4143", "fetched_at": "2026-08-28T04:06:28.960015+00:00", "kind": "readme", "missing": false, "url": "https://github.com/WillKoehrsen/feature-selector"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-30T02:44:41.969440+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "05b075d505926efdd78162a08029c2a4fa807706b30cc5fbdeb43ba7c43d4143", "fetched_at": "2026-08-28T04:06:28.960015+00:00", "kind": "readme", "missing": false, "url": "https://github.com/WillKoehrsen/feature-selector"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:06:28.960015+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:06:28.960015+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:06:28.960015+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-30T02:44:41.969440+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "05b075d505926efdd78162a08029c2a4fa807706b30cc5fbdeb43ba7c43d4143", "fetched_at": "2026-08-28T04:06:28.960015+00:00", "kind": "readme", "missing": false, "url": "https://github.com/WillKoehrsen/feature-selector"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:06:28.960015+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:06:28.960015+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-30T02:44:41.969440+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "05b075d505926efdd78162a08029c2a4fa807706b30cc5fbdeb43ba7c43d4143", "fetched_at": "2026-08-28T04:06:28.960015+00:00", "kind": "readme", "missing": false, "url": "https://github.com/WillKoehrsen/feature-selector"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:06:28.960015+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:06:28.960015+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:06:28.960015+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-30T02:44:41.969440+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "05b075d505926efdd78162a08029c2a4fa807706b30cc5fbdeb43ba7c43d4143", "fetched_at": "2026-08-28T04:06:28.960015+00:00", "kind": "readme", "missing": false, "url": "https://github.com/WillKoehrsen/feature-selector"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:06:28.960015+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:06:28.960015+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-30T02:44:41.969440+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "05b075d505926efdd78162a08029c2a4fa807706b30cc5fbdeb43ba7c43d4143", "fetched_at": "2026-08-28T04:06:28.960015+00:00", "kind": "readme", "missing": false, "url": "https://github.com/WillKoehrsen/feature-selector"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-30T02:44:41.969440+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "05b075d505926efdd78162a08029c2a4fa807706b30cc5fbdeb43ba7c43d4143", "fetched_at": "2026-08-28T04:06:28.960015+00:00", "kind": "readme", "missing": false, "url": "https://github.com/WillKoehrsen/feature-selector"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-30T02:44:41.969440+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "05b075d505926efdd78162a08029c2a4fa807706b30cc5fbdeb43ba7c43d4143", "fetched_at": "2026-08-28T04:06:28.960015+00:00", "kind": "readme", "missing": false, "url": "https://github.com/WillKoehrsen/feature-selector"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-30T02:44:41.969440+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "05b075d505926efdd78162a08029c2a4fa807706b30cc5fbdeb43ba7c43d4143", "fetched_at": "2026-08-28T04:06:28.960015+00:00", "kind": "readme", "missing": false, "url": "https://github.com/WillKoehrsen/feature-selector"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 0, "longevity": 100, "rhythm": 35}, "computed_at": "2026-09-03T02:20:16.233290+00:00", "flags": ["no_releases"], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 2996, "days_push": 807, "days_rel": null, "gap_med": null, "n_releases_24m": 0}, "score": 32, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}