{"id":17384552,"url":"https://github.com/pgdr/mood","last_synced_at":"2025-03-27T21:18:37.766Z","repository":{"id":139058534,"uuid":"59987930","full_name":"pgdr/mood","owner":"pgdr","description":null,"archived":false,"fork":false,"pushed_at":"2016-05-30T09:39:19.000Z","size":28,"stargazers_count":0,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-02-01T23:42:08.227Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/pgdr.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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":"2016-05-30T07:03:04.000Z","updated_at":"2016-05-30T07:09:52.000Z","dependencies_parsed_at":null,"dependency_job_id":"6b7893ed-c49a-409c-b11e-b3d417452909","html_url":"https://github.com/pgdr/mood","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/pgdr%2Fmood","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pgdr%2Fmood/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pgdr%2Fmood/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pgdr%2Fmood/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/pgdr","download_url":"https://codeload.github.com/pgdr/mood/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245924501,"owners_count":20694731,"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":"2024-10-16T07:45:50.624Z","updated_at":"2025-03-27T21:18:37.743Z","avatar_url":"https://github.com/pgdr.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# mood, in a sentimental\n\nThis program takes two folders \"pos\" and \"neg\" containing positive\n(resp. negative) text files and learn to predict the mood of a new text file.\n\nThe algorithm proceeds as follows:\n* Tokenize, lemmatize and remove stop words for every data point\n* Pick up 1000 \"good\" words (how?)\n* Create a vector consisting of 1000 words\n* For each input data file, construct a 1000 dimensional boolean vector being the characteristic function of the words vector\n* Train an SVM (with radial basis function (Gaussian) kernel) on the dataset\n* ???\n* Predict.\n\nUsing 20% cross validation (will update to 10-fold CV later) the predictor today\n(with the given words.txt file) achieves ~80% correctness.\n\nThere is also a PCA implementation which maps the dataset to a 2 and 3\ndimensional hyperplane and visualizes that using matplotlib.\n\nThe PCA in 2D (here is a [visualization of the 3D plot](https://gfycat.com/SingleVerifiableDiscus)):\n\n![2D PCA](http://i.stack.imgur.com/4Uxya.png)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpgdr%2Fmood","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpgdr%2Fmood","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpgdr%2Fmood/lists"}