{"id":20846924,"url":"https://github.com/amiraflak/data-mining","last_synced_at":"2025-08-10T04:44:10.044Z","repository":{"id":255746368,"uuid":"787881793","full_name":"AmirAflak/Data-Mining","owner":"AmirAflak","description":"Data Mining Course - Spring 2024","archived":false,"fork":false,"pushed_at":"2024-09-06T19:52:18.000Z","size":769,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-12T11:49:01.262Z","etag":null,"topics":["classification","clustering","data-analysis","data-mining","decision-tree-classifier","eda","pca"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","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/AmirAflak.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":"2024-04-17T11:09:57.000Z","updated_at":"2024-09-06T19:55:54.000Z","dependencies_parsed_at":"2024-09-07T00:17:27.219Z","dependency_job_id":"6723efc9-faae-4f61-a662-233374a77a51","html_url":"https://github.com/AmirAflak/Data-Mining","commit_stats":null,"previous_names":["amiraflak/data-mining"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/AmirAflak/Data-Mining","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AmirAflak%2FData-Mining","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AmirAflak%2FData-Mining/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AmirAflak%2FData-Mining/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AmirAflak%2FData-Mining/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/AmirAflak","download_url":"https://codeload.github.com/AmirAflak/Data-Mining/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AmirAflak%2FData-Mining/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":269677513,"owners_count":24457858,"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","status":"online","status_checked_at":"2025-08-10T02:00:08.965Z","response_time":71,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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":["classification","clustering","data-analysis","data-mining","decision-tree-classifier","eda","pca"],"created_at":"2024-11-18T02:18:28.085Z","updated_at":"2025-08-10T04:44:09.992Z","avatar_url":"https://github.com/AmirAflak.png","language":"Jupyter Notebook","readme":"# Data Mining Project\r\nThis project develops a machine learning model to classify customers based on their features and predict whether they will make a deposit into their newly opened account, using a dataset from a Portuguese bank's marketing campaign.\r\n- Data Mining Course - Spring 2024\r\n\r\n\r\n## Dataset Description\r\nThe dataset represents a marketing campaign by a Portuguese bank, containing customer information.\r\nThe dataset contains 11162 samples, with 16 features. The features include:\r\n- Demographic information: age, job, marital status, education\r\n- Financial information: default, housing, loan\r\n- Marketing campaign information: contact, month, day of week, duration, campaign, pdays, previous, poutcome\r\n- Target variable: deposit (binary categorical)\r\n\r\n## Exploratory Data Analysis (EDA)\r\nThe EDA notebook provides an exploratory data analysis of the dataset, including:\r\n- Data cleaning and preprocessing\r\n- Visualization of the data using various plots and charts\r\n\r\n## Classification \r\nThe classification notebook develops a machine learning model to classify customers based on their observed features. The model is trained using a variety of algorithms, including KNN and decision trees. The performance of each model is evaluated using metrics such as accuracy, precision, and recall.\r\n\r\n## Clustering \r\nThe clustering notebook applies clustering algorithms to the dataset to identify patterns and group similar customers together. The algorithms used include k-means and hierarchical clustering. The results of the clustering analysis are visualized using various plots and charts.\r\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Famiraflak%2Fdata-mining","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Famiraflak%2Fdata-mining","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Famiraflak%2Fdata-mining/lists"}