{"id":20271728,"url":"https://github.com/rodneyshag/documentclassification","last_synced_at":"2025-04-11T04:32:40.531Z","repository":{"id":123421738,"uuid":"78978584","full_name":"RodneyShag/DocumentClassification","owner":"RodneyShag","description":"Spam classification and sentiment analysis on text documents.","archived":false,"fork":false,"pushed_at":"2017-06-11T21:23:29.000Z","size":2234,"stargazers_count":3,"open_issues_count":0,"forks_count":4,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-04-11T04:32:25.682Z","etag":null,"topics":["machine-learning","naive-bayes-classifier","sentiment-analysis","spam-classification"],"latest_commit_sha":null,"homepage":"","language":"Java","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/RodneyShag.png","metadata":{"files":{"readme":"README.md","changelog":"news/8category.testing.txt","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":"2017-01-14T23:57:30.000Z","updated_at":"2019-05-03T07:13:21.000Z","dependencies_parsed_at":null,"dependency_job_id":"e537bd3a-a705-4264-946f-bd564f70b86a","html_url":"https://github.com/RodneyShag/DocumentClassification","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/RodneyShag%2FDocumentClassification","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RodneyShag%2FDocumentClassification/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RodneyShag%2FDocumentClassification/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RodneyShag%2FDocumentClassification/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/RodneyShag","download_url":"https://codeload.github.com/RodneyShag/DocumentClassification/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248345202,"owners_count":21088231,"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":["machine-learning","naive-bayes-classifier","sentiment-analysis","spam-classification"],"created_at":"2024-11-14T12:39:13.220Z","updated_at":"2025-04-11T04:32:40.490Z","avatar_url":"https://github.com/RodneyShag.png","language":"Java","funding_links":[],"categories":[],"sub_categories":[],"readme":"# DocumentClassification\nSpam classification and sentiment analysis.\n\n## Goals:\n1) **Spam Classification:** Partition emails into 2 categories depending on whether they contain spam or not.\u003cbr/\u003e\n2) **Sentiment Analysis:** Partition movie reviews into 2 categories depending on whether they are positive or negative reviews.\n\n## Classifiers:\n1) [Multinomial Naive Bayes](https://en.wikipedia.org/wiki/Naive_Bayes_classifier#Multinomial_naive_Bayes)\u003cbr/\u003e\n2) [Bernoulli Naive Bayes](https://en.wikipedia.org/wiki/Naive_Bayes_classifier#Bernoulli_naive_Bayes)\n\n## Data Formats:\n1) **emails:** text documents\u003cbr/\u003e\n2) **movie reviews:** text documents\n\n## Technique:\nThe goals above are each accomplished by training a Naive Bayes classifier on a set of training data, and then testing our classifier on a set of test data. We hope to have a high success rate in figuring out which emails contain spam, and whether an unseen movie review is positive or negative.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frodneyshag%2Fdocumentclassification","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frodneyshag%2Fdocumentclassification","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frodneyshag%2Fdocumentclassification/lists"}