{"id":15787242,"url":"https://github.com/ysig/kml_2021","last_synced_at":"2025-03-31T17:48:40.456Z","repository":{"id":120701431,"uuid":"351150186","full_name":"ysig/kml_2021","owner":"ysig","description":"Submission code for kml_2021","archived":false,"fork":false,"pushed_at":"2021-03-25T00:43:38.000Z","size":1058,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2024-10-05T21:06:44.520Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ysig.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2021-03-24T16:30:03.000Z","updated_at":"2021-03-25T00:43:40.000Z","dependencies_parsed_at":"2024-08-11T11:30:47.384Z","dependency_job_id":null,"html_url":"https://github.com/ysig/kml_2021","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ysig%2Fkml_2021","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ysig%2Fkml_2021/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ysig%2Fkml_2021/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ysig%2Fkml_2021/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ysig","download_url":"https://codeload.github.com/ysig/kml_2021/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246512880,"owners_count":20789796,"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":"2024-10-04T21:06:45.755Z","updated_at":"2025-03-31T17:48:40.413Z","avatar_url":"https://github.com/ysig.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# kernels-2021\nKaggle-Ranking of Kernels (**Public Leaderboard**):\n\n| Method  | Kaggle Accuracy |\n| ------------- | ------------- |\n| Linear-Regression  |  0.60466  |\n| SVM  | 0.55866  |\n| Kernel-Ridge-Regression | 0.61933 |\n| Spectrum (k=6) | 0.62600 |\n| Gappy (q=8, l=6) | 0.62866  |\n| mismatch (m=1, k=8) | 0.65400 |\n| mismatch (m=1, k=9) | 0.67333 |\n\n**Final Ranking**  \nPrivate Leaderboard: 0.67733  \n(mismatch (m=1, k=9))\n\n# Details about this code-base\n\nDependencies: cvxopt, scipy, numpy\n\nYou can run main.py as:\n    `python main.py`\nor with:\n    `python main.py --dry`\nfor validation. In the latter case it needs `sciki-learn` for `train_test_split` and `accuracy_report`.\nAll the submitted kaggle files are in folder `predictions` and all the logs from validation are in the folder `logs`.\nYou can find the extensive evaluation logs with the most promising of the tested kernel parameters and C from 2^{-2}, ..., 2^{2} in \n\nThe only kernel that is not in validation and in predictions and which has been implemented is the substring kernel, which\ncan be found at `substring.py`.\n\nFiles corresponding to kernels:\n - `spectrum.py`\n - `svm.py` and `gaussian.py`\n - `gappy.py`\n - `mismatch.py`\n - `substring.py`\n\nFiles corresponding to classifiers:\n - `kernel_svm.py`\n - `ridge_regression.py`\n - `kernel_ridge_regression.py`\n\nOther files:\n - `training.py` corresponds to all the train and predict pipeline, for all methods.\n - `classes.py` used to define base classes for kernels and classifiers.\n - `argparser.py` used to define the simple command line argument of dry.\n - `utils.py` used to define a thresholding function.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fysig%2Fkml_2021","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fysig%2Fkml_2021","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fysig%2Fkml_2021/lists"}