{"id":21717118,"url":"https://github.com/tathithienthanh/datamining-banking-dataset","last_synced_at":"2026-04-20T09:03:09.577Z","repository":{"id":220468707,"uuid":"751717551","full_name":"tathithienthanh/DataMining-Banking-Dataset","owner":"tathithienthanh","description":"Implement some learned data mining techniques and predict if the client will subscribe to a term deposit","archived":false,"fork":false,"pushed_at":"2024-02-02T07:37:50.000Z","size":3338,"stargazers_count":2,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-25T18:11:22.637Z","etag":null,"topics":["apriori","association-rules","classification","clustering","data-analysis","data-mining","data-processing","google-colab","ipynb","kmeans","naive-bayes","py","python","scikit-learn","svm","visualization"],"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/tathithienthanh.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}},"created_at":"2024-02-02T07:05:34.000Z","updated_at":"2024-10-21T16:27:32.000Z","dependencies_parsed_at":"2024-02-02T08:44:23.989Z","dependency_job_id":null,"html_url":"https://github.com/tathithienthanh/DataMining-Banking-Dataset","commit_stats":null,"previous_names":["thienthanhtt/datamining-banking-dataset","tathithienthanh/datamining-banking-dataset"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tathithienthanh%2FDataMining-Banking-Dataset","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tathithienthanh%2FDataMining-Banking-Dataset/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tathithienthanh%2FDataMining-Banking-Dataset/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tathithienthanh%2FDataMining-Banking-Dataset/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/tathithienthanh","download_url":"https://codeload.github.com/tathithienthanh/DataMining-Banking-Dataset/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":244681243,"owners_count":20492760,"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":["apriori","association-rules","classification","clustering","data-analysis","data-mining","data-processing","google-colab","ipynb","kmeans","naive-bayes","py","python","scikit-learn","svm","visualization"],"created_at":"2024-11-26T01:15:23.339Z","updated_at":"2026-04-20T09:03:04.554Z","avatar_url":"https://github.com/tathithienthanh.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# DataMining-Banking-Dataset\n\nImplement some learned data mining techniques and predict if the client will subscribe to a term deposit\n\n# Citation\nThis dataset is publicly available for research. It has been picked up from the UCI Machine Learning with random sampling and a few additional columns.\n\nPlease add this citation if you use this dataset for any further analysis.\n\n*S. Moro, P. Cortez and P. Rita. A Data-Driven Approach to Predict the Success of Bank Telemarketing. Decision Support Systems, Elsevier, 62:22-31, June 2014*\n\n# Past Usage\nThe full dataset was described and analyzed in:\n\n* S. Moro, R. Laureano and P. Cortez. Using Data Mining for Bank Direct Marketing: An Application of the CRISP-DM Methodology.\n* In P. Novais et al. (Eds.), Proceedings of the European Simulation and Modelling Conference - ESM'2011, pp. 117-121, Guimarães, Portugal, October, 2011. EUROSIS.\n\n# Detailed Information about the dataset\nhttps://www.kaggle.com/code/santhoshtsk/banking-dataset-analysis-and-prediction/input\n\n# About the report and code\n* Used techniques: preprocessing, clustering with K-Means, association rule with apriori, classification with Gaussian Naive Bayes and SVM, ...\n* Re-edit the path if you use our code for importing or loading the dataset.\n* The report is submitted and scored by the instructor.\n* The report is for reference only, please do not edit or use for other purposes.\n\n*All the files are done by me and @phamcongthuan, if you reuse the code please add the citation*\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftathithienthanh%2Fdatamining-banking-dataset","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftathithienthanh%2Fdatamining-banking-dataset","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftathithienthanh%2Fdatamining-banking-dataset/lists"}