{"payload":{"pageCount":1,"repositories":[{"type":"Public","name":"qolmat","owner":"scikit-learn-contrib","isFork":false,"description":"A scikit-learn-compatible module for comparing imputation methods.","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":4,"issueCount":3,"starsCount":133,"forksCount":2,"license":"BSD 3-Clause \"New\" or \"Revised\" License","participation":[41,25,33,24,11,16,14,17,6,3,20,14,20,26,14,23,28,17,21,30,18,0,0,0,2,1,0,0,0,0,0,0,0,0,4,2,15,0,6,3,4,0,10,33,0,0,0,0,0,0,0,0],"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-06-12T22:27:04.369Z"}},{"type":"Public","name":"MAPIE","owner":"scikit-learn-contrib","isFork":false,"description":"A scikit-learn-compatible module to estimate prediction intervals and control risks based on conformal predictions.","allTopics":["python","data-science","sklearn","regression","classification","confidence-intervals","conformal-prediction"],"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":14,"issueCount":34,"starsCount":1189,"forksCount":98,"license":"BSD 3-Clause \"New\" or \"Revised\" License","participation":[26,15,23,72,29,51,20,16,6,7,35,42,55,20,18,37,4,3,6,0,0,21,0,3,1,19,21,17,42,7,32,8,2,4,9,0,5,11,0,0,0,0,2,15,31,1,17,23,48,19,6,15],"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-06-12T15:44:18.548Z"}},{"type":"Public","name":"sklearn-ann","owner":"scikit-learn-contrib","isFork":false,"description":"Integration with (approximate) nearest neighbors libraries for scikit-learn + clustering based on with kNN-graphs.","allTopics":["clustering","scikit-learn","approximate-nearest-neighbor-search","knn","knn-graphs"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":9,"starsCount":14,"forksCount":3,"license":"BSD 3-Clause \"New\" or \"Revised\" License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-06-11T07:36:22.490Z"}},{"type":"Public","name":"scikit-matter","owner":"scikit-learn-contrib","isFork":false,"description":"A collection of scikit-learn compatible utilities that implement methods born out of the materials science and chemistry communities","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":4,"issueCount":13,"starsCount":69,"forksCount":17,"license":"BSD 3-Clause \"New\" or \"Revised\" License","participation":[0,0,3,1,0,1,12,3,5,4,5,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,4,0,6,5,0,0],"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-06-10T23:24:36.019Z"}},{"type":"Public","name":"skglm","owner":"scikit-learn-contrib","isFork":false,"description":"Fast and modular sklearn replacement for generalized linear models","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":15,"issueCount":39,"starsCount":139,"forksCount":28,"license":"BSD 3-Clause \"New\" or \"Revised\" License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-06-10T19:57:12.952Z"}},{"type":"Public","name":"boruta_py","owner":"scikit-learn-contrib","isFork":false,"description":"Python implementations of the Boruta all-relevant feature selection method.","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":5,"issueCount":38,"starsCount":1454,"forksCount":250,"license":"BSD 3-Clause \"New\" or \"Revised\" License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-06-10T08:03:53.096Z"}},{"type":"Public","name":"scikit-dimension","owner":"scikit-learn-contrib","isFork":false,"description":" A Python package for intrinsic dimension estimation","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":6,"starsCount":72,"forksCount":15,"license":"BSD 3-Clause \"New\" or \"Revised\" License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-06-09T14:54:39.109Z"}},{"type":"Public template","name":"project-template","owner":"scikit-learn-contrib","isFork":false,"description":"A template for scikit-learn extensions","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":1,"starsCount":313,"forksCount":91,"license":"BSD 3-Clause \"New\" or \"Revised\" License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-06-06T15:29:32.845Z"}},{"type":"Public","name":"imbalanced-learn","owner":"scikit-learn-contrib","isFork":false,"description":" A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning","allTopics":["data-science","machine-learning","statistics","data-analysis","python"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":15,"issueCount":26,"starsCount":6738,"forksCount":1274,"license":"MIT License","participation":[0,0,0,38,0,0,0,1,0,0,0,0,2,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,2,0,0],"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-05-28T15:13:16.067Z"}},{"type":"Public","name":"hdbscan","owner":"scikit-learn-contrib","isFork":false,"description":"A high performance implementation of HDBSCAN clustering.","allTopics":["machine-learning","clustering","machine-learning-algorithms","cluster-analysis","clustering-algorithm","clustering-evaluation"],"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":21,"issueCount":333,"starsCount":2712,"forksCount":489,"license":"BSD 3-Clause \"New\" or \"Revised\" License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-05-24T16:21:00.088Z"}},{"type":"Public","name":"scikit-learn-extra","owner":"scikit-learn-contrib","isFork":false,"description":"scikit-learn contrib estimators","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":14,"issueCount":25,"starsCount":185,"forksCount":42,"license":"BSD 3-Clause \"New\" or \"Revised\" License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-05-19T22:00:10.013Z"}},{"type":"Public","name":"denmune-clustering-algorithm","owner":"scikit-learn-contrib","isFork":false,"description":"DenMune a clustering algorithm that can find clusters of arbitrary size, shapes and densities in two-dimensions. Higher dimensions are first reduced to 2-D using the t-sne. The algorithm relies on a single parameter K (the number of nearest neighbors). The results show the superiority of DenMune. Enjoy the simplicty but the power of DenMune.","allTopics":["python","machine-learning","deep-learning","clustering"],"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":0,"issueCount":0,"starsCount":28,"forksCount":8,"license":"BSD 3-Clause \"New\" or \"Revised\" License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-05-10T16:49:53.691Z"}},{"type":"Public","name":"hiclass","owner":"scikit-learn-contrib","isFork":false,"description":"A python library for hierarchical classification compatible with scikit-learn","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":7,"issueCount":12,"starsCount":105,"forksCount":17,"license":"BSD 3-Clause \"New\" or \"Revised\" License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-05-05T12:43:03.603Z"}},{"type":"Public","name":"DESlib","owner":"scikit-learn-contrib","isFork":false,"description":"A Python library for dynamic classifier and ensemble selection","allTopics":["diversity","ensemble-learning","ensemble-prediction","ensemble-selection","diversity-measures","dynamic-ensembles","classifier-ensembles","dynamic-selection"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":1,"issueCount":15,"starsCount":473,"forksCount":106,"license":"BSD 3-Clause \"New\" or \"Revised\" License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-15T06:19:14.488Z"}},{"type":"Public","name":"category_encoders","owner":"scikit-learn-contrib","isFork":false,"description":"A library of sklearn compatible categorical variable encoders","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":1,"issueCount":45,"starsCount":2381,"forksCount":393,"license":"BSD 3-Clause \"New\" or \"Revised\" License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-09T11:39:30.730Z"}},{"type":"Public","name":"skope-rules","owner":"scikit-learn-contrib","isFork":false,"description":"machine learning with logical rules in Python","allTopics":[],"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":5,"issueCount":29,"starsCount":596,"forksCount":95,"license":"Other","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-01-31T14:01:51.289Z"}},{"type":"Public","name":"metric-learn","owner":"scikit-learn-contrib","isFork":false,"description":"Metric learning algorithms in Python","allTopics":["machine-learning","scikit-learn","metric-learning","python"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":10,"issueCount":43,"starsCount":1383,"forksCount":232,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-10-09T07:21:10.489Z"}},{"type":"Public archive","name":"py-earth","owner":"scikit-learn-contrib","isFork":false,"description":"A Python implementation of Jerome Friedman's Multivariate Adaptive Regression Splines","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":6,"issueCount":46,"starsCount":455,"forksCount":121,"license":"BSD 3-Clause \"New\" or \"Revised\" License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-08-14T22:12:49.549Z"}},{"type":"Public archive","name":"lightning","owner":"scikit-learn-contrib","isFork":false,"description":"Large-scale linear classification, regression and ranking in Python","allTopics":["machine-learning"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":7,"issueCount":49,"starsCount":1708,"forksCount":213,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-07-18T11:41:11.901Z"}},{"type":"Public","name":"sklearn-pandas","owner":"scikit-learn-contrib","isFork":false,"description":"Pandas integration with sklearn","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":10,"issueCount":28,"starsCount":2789,"forksCount":414,"license":"Other","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-06-08T06:48:29.606Z"}},{"type":"Public archive","name":"stability-selection","owner":"scikit-learn-contrib","isFork":false,"description":"scikit-learn compatible implementation of stability selection.","allTopics":["machine-learning","statistics","feature-selection","scikit-learn"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":4,"issueCount":15,"starsCount":207,"forksCount":63,"license":"BSD 3-Clause \"New\" or \"Revised\" License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-06-05T03:59:59.507Z"}},{"type":"Public","name":"scikit-learn-contrib","owner":"scikit-learn-contrib","isFork":false,"description":"scikit-learn compatible projects","allTopics":[],"primaryLanguage":null,"pullRequestCount":1,"issueCount":18,"starsCount":407,"forksCount":50,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-11-08T08:57:24.742Z"}},{"type":"Public","name":"skdag","owner":"scikit-learn-contrib","isFork":false,"description":"A more flexible alternative to scikit-learn Pipelines","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":4,"starsCount":28,"forksCount":6,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-09-09T21:34:56.764Z"}},{"type":"Public","name":"forest-confidence-interval","owner":"scikit-learn-contrib","isFork":false,"description":"Confidence intervals for scikit-learn forest algorithms","allTopics":[],"primaryLanguage":{"name":"HTML","color":"#e34c26"},"pullRequestCount":1,"issueCount":19,"starsCount":282,"forksCount":46,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-09-09T15:23:20.168Z"}},{"type":"Public archive","name":"polylearn","owner":"scikit-learn-contrib","isFork":false,"description":"A library for factorization machines and polynomial networks for classification and regression in Python.","allTopics":["machine-learning","factorization-machines","polynomial-regression","polynomial-networks"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":1,"issueCount":8,"starsCount":245,"forksCount":43,"license":"BSD 2-Clause \"Simplified\" License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-08-07T12:55:30.862Z"}},{"type":"Public archive","name":"mimic","owner":"scikit-learn-contrib","isFork":false,"description":"mimic calibration","allTopics":["machine-learning","calibration"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":21,"forksCount":6,"license":"BSD 3-Clause \"New\" or \"Revised\" License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2019-10-16T22:42:43.100Z"}},{"type":"Public","name":"scikit-learn-contrib.github.io","owner":"scikit-learn-contrib","isFork":false,"description":"Project webpage","allTopics":[],"primaryLanguage":{"name":"HTML","color":"#e34c26"},"pullRequestCount":0,"issueCount":0,"starsCount":4,"forksCount":1,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2016-08-08T14:03:26.702Z"}}],"repositoryCount":27,"userInfo":null,"searchable":true,"definitions":[],"typeFilters":[{"id":"all","text":"All"},{"id":"public","text":"Public"},{"id":"source","text":"Sources"},{"id":"fork","text":"Forks"},{"id":"archived","text":"Archived"},{"id":"template","text":"Templates"}],"compactMode":false},"title":"Repositories"}