{"id":23166,"library":"sklearn-evaluation","title":"sklearn-evaluation","description":"A Python library for evaluating scikit-learn models, providing a rich set of plots, tables, and markdown reports. Current version 0.12.2. Released irregularly; latest releases are minor patches.","status":"active","version":"0.12.2","language":"python","source_language":"en","source_url":"https://github.com/ploomber/sklearn-evaluation","tags":["scikit-learn","model-evaluation","plots","reports","machine-learning"],"install":[{"cmd":"pip install sklearn-evaluation","lang":"bash","label":"Install via pip"}],"dependencies":[{"reason":"Core dependency for model evaluation","package":"scikit-learn","optional":false},{"reason":"Required for plotting","package":"matplotlib","optional":false},{"reason":"Used for data manipulation and tables","package":"pandas","optional":false}],"imports":[{"wrong":"from sklearn_evaluation import ClassificationReport","symbol":"ClassifierEvaluator","correct":"from sklearn_evaluation import ClassifierEvaluator"}],"quickstart":{"code":"from sklearn.datasets import make_classification\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.ensemble import RandomForestClassifier\nfrom sklearn_evaluation import ClassificationReport\n\nX, y = make_classification(random_state=0)\nX_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)\nclf = RandomForestClassifier(random_state=0)\nclf.fit(X_train, y_train)\ny_pred = clf.predict(X_test)\n\nreport = ClassificationReport(y_test, y_pred)\nprint(report)\nreport.plot()","lang":"python","description":"Train a Random Forest classifier and generate a classification report."},"warnings":[{"fix":"Use 'from sklearn_evaluation import ...'","message":"Import from 'sklearn_evaluation' with underscores, not 'sklearn-evaluation' (hyphen). The package name on PyPI uses a hyphen, but the import uses an underscore.","severity":"gotcha","affected_versions":"all"},{"fix":"Use classes like ClassificationReport, ConfusionMatrix, etc.","message":"Version 0.5 introduced a new API for reports, deprecating the old 'sklearn_evaluation.plot.*' functions. Users should use the new object-oriented API (e.g., ClassificationReport, ConfusionMatrix) instead of the old functional interface.","severity":"deprecated","affected_versions":">=0.5"},{"fix":"Migrate to the new API: from sklearn_evaluation import ClassificationReport","message":"In version 0.5, the report generation API changed. Old code using 'sklearn_evaluation.report' may break.","severity":"breaking","affected_versions":"<0.5 to >=0.5"}],"env_vars":null,"search_vec":"'0.12.2':25 'current':23 'evalu':3,8,38 'irregular':27 'latest':28 'learn':11,35,43 'librari':6 'machin':42 'machine-learn':41 'markdown':21 'minor':31 'model':12,37 'model-evalu':36 'patch':32 'plot':18,39 'provid':13 'python':5 'releas':26,29 'report':22,40 'rich':15 'scikit':10,34 'scikit-learn':9,33 'set':16 'sklearn':2 'sklearn-evalu':1 'tabl':19 'version':24","created_at":"2026-05-01T06:02:46.200572+00:00","updated_at":"2026-05-01T06:02:46.200572+00:00","problems":null,"ecosystem":"pypi","meta_description":null,"install_score":null,"quickstart_score":null,"quickstart_tag":null,"pypi_latest":"0.12.2","cli_name":"","cli_version":null,"type":"library","homepage":null,"github":"https://github.com/ploomber/sklearn-evaluation","docs":null,"changelog":null,"pypi":"https://pypi.org/project/sklearn-evaluation/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"categories":["ai-ml"],"base_url":null,"auth_type":null,"provenance":{"verified_status":"passing","verified_at":"2026-07-03","last_verified":"2026-07-03","next_check":"2026-08-02","install_tag":null}}