{"id":13486982,"url":"https://github.com/larsmans/seqlearn","last_synced_at":"2025-05-16T13:05:49.682Z","repository":{"id":50469069,"uuid":"11797696","full_name":"larsmans/seqlearn","owner":"larsmans","description":"Sequence learning toolkit for Python","archived":false,"fork":false,"pushed_at":"2023-03-24T08:01:57.000Z","size":881,"stargazers_count":694,"open_issues_count":33,"forks_count":101,"subscribers_count":39,"default_branch":"master","last_synced_at":"2025-04-09T08:05:46.283Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"http://larsmans.github.io/seqlearn/","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/larsmans.png","metadata":{"files":{"readme":"README.rst","changelog":null,"contributing":null,"funding":null,"license":"COPYING","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2013-07-31T18:15:59.000Z","updated_at":"2025-04-08T03:59:21.000Z","dependencies_parsed_at":"2023-02-10T12:15:30.638Z","dependency_job_id":"c3ef055d-eede-4156-8613-7a6b18d3e94e","html_url":"https://github.com/larsmans/seqlearn","commit_stats":{"total_commits":88,"total_committers":3,"mean_commits":"29.333333333333332","dds":0.09090909090909094,"last_synced_commit":"32d4bfaebdd877733f180ea6072e8fc1266bc559"},"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/larsmans%2Fseqlearn","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/larsmans%2Fseqlearn/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/larsmans%2Fseqlearn/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/larsmans%2Fseqlearn/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/larsmans","download_url":"https://codeload.github.com/larsmans/seqlearn/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":253292124,"owners_count":21885037,"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":[],"created_at":"2024-07-31T18:00:54.058Z","updated_at":"2025-05-16T13:05:49.635Z","avatar_url":"https://github.com/larsmans.png","language":"Python","readme":".. -*- mode: rst -*-\n\nseqlearn\n========\n\nseqlearn is a sequence classification toolkit for Python. It is designed to\nextend `scikit-learn \u003chttp://scikit-learn.org\u003e`_ and offer as similar as\npossible an API.\n\n\nCompiling and installing\n------------------------\n\nGet NumPy \u003e=1.6, SciPy \u003e=0.11, Cython \u003e=0.20.2 and a recent version of\nscikit-learn. Then issue::\n\n    python setup.py install\n\nto install seqlearn.\n\nIf you want to use seqlearn from its source directory without installing,\nyou have to compile first::\n\n    python setup.py build_ext --inplace\n\n\nGetting started\n---------------\n\nThe easiest way to start using seqlearn is to fetch a dataset in CoNLL 2000\nformat. Define a task-specific feature extraction function, e.g.::\n\n    \u003e\u003e\u003e def features(sequence, i):\n    ...     yield \"word=\" + sequence[i].lower()\n    ...     if sequence[i].isupper():\n    ...         yield \"Uppercase\"\n    ...\n\nLoad the training file, say ``train.txt``::\n\n    \u003e\u003e\u003e from seqlearn.datasets import load_conll\n    \u003e\u003e\u003e X_train, y_train, lengths_train = load_conll(\"train.txt\", features)\n\nTrain a model::\n\n    \u003e\u003e\u003e from seqlearn.perceptron import StructuredPerceptron\n    \u003e\u003e\u003e clf = StructuredPerceptron()\n    \u003e\u003e\u003e clf.fit(X_train, y_train, lengths_train)\n\nCheck how well you did on a validation set, say ``validation.txt``::\n\n    \u003e\u003e\u003e X_test, y_test, lengths_test = load_conll(\"validation.txt\", features)\n    \u003e\u003e\u003e from seqlearn.evaluation import bio_f_score\n    \u003e\u003e\u003e y_pred = clf.predict(X_test, lengths_test)\n    \u003e\u003e\u003e print(bio_f_score(y_test, y_pred))\n\nFor more information, see the `documentation\n\u003chttp://larsmans.github.io/seqlearn\u003e`_.\n\n\n|Travis|_\n\n.. |Travis| image:: https://api.travis-ci.org/larsmans/seqlearn.png?branch=master\n.. _Travis: https://travis-ci.org/larsmans/seqlearn\n","funding_links":[],"categories":["The Data Science Toolbox","Python","Machine Learning"],"sub_categories":["General Machine Learning Packages","General Purpose Machine Learning","Automatic Plotting"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flarsmans%2Fseqlearn","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flarsmans%2Fseqlearn","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flarsmans%2Fseqlearn/lists"}