{"id":26502184,"url":"https://github.com/saadhaniftaj/logistic--lasso-regression-data-analysis","last_synced_at":"2026-05-18T08:05:46.200Z","repository":{"id":262313517,"uuid":"886300415","full_name":"saadhaniftaj/logistic--lasso-regression-data-analysis","owner":"saadhaniftaj","description":"Iris dataset analysis with logistic and Lasso regression, using coordinate descent for feature selection and binary classification. Includes preprocessing and data visualizations","archived":false,"fork":false,"pushed_at":"2024-11-11T18:32:21.000Z","size":76,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-20T17:45:54.960Z","etag":null,"topics":["data-analysis","lasso-regression-model","logistic-regression","python","statistics"],"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/saadhaniftaj.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":"2024-11-10T17:50:47.000Z","updated_at":"2024-11-11T18:32:24.000Z","dependencies_parsed_at":"2024-11-16T21:01:58.651Z","dependency_job_id":null,"html_url":"https://github.com/saadhaniftaj/logistic--lasso-regression-data-analysis","commit_stats":null,"previous_names":["saadhaniftaj/logistic--lasso-regression-data-analysis"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/saadhaniftaj/logistic--lasso-regression-data-analysis","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saadhaniftaj%2Flogistic--lasso-regression-data-analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saadhaniftaj%2Flogistic--lasso-regression-data-analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saadhaniftaj%2Flogistic--lasso-regression-data-analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saadhaniftaj%2Flogistic--lasso-regression-data-analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/saadhaniftaj","download_url":"https://codeload.github.com/saadhaniftaj/logistic--lasso-regression-data-analysis/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saadhaniftaj%2Flogistic--lasso-regression-data-analysis/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":33170446,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-18T05:43:36.989Z","status":"ssl_error","status_checked_at":"2026-05-18T05:43:19.133Z","response_time":71,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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":["data-analysis","lasso-regression-model","logistic-regression","python","statistics"],"created_at":"2025-03-20T17:37:13.729Z","updated_at":"2026-05-18T08:05:46.159Z","avatar_url":"https://github.com/saadhaniftaj.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Iris Dataset Analysis with Coordinate Descent\n\n## Overview\nThis project explores the Iris dataset, focusing on:\n1. **Binary Classification**: Using Logistic Regression and coordinate descent to classify two species.\n2. **Feature Selection**: Applying Lasso regression with coordinate descent to select key features predicting petal length.\n3. **Data Visualization**: Displaying distributions and relationships between features.\n\n## Project Structure\n- **Data Preprocessing**: Cleans and encodes the Iris dataset, making it ready for machine learning.\n- **Coordinate Descent for Logistic Regression**: Implements a logistic regression classifier for a binary subset of species in the Iris dataset.\n- **Lasso Regression for Feature Selection**: Uses Lasso regularization to identify important features for predicting petal length.\n- **Visualization**: Provides histograms and scatter plots to illustrate feature distributions and relationships.\n\n## How to Run\n1. Clone or download this repository.\n2. Open the notebook `DS_221_Project.ipynb` in Jupyter Notebook or Jupyter Lab.\n3. Run each cell sequentially to see preprocessing, analysis, and visualizations.\n\n## Requirements\n- Python 3.x\n- Libraries: `pandas`, `numpy`, `scikit-learn`, `matplotlib`\n\n## Key Results\n- **Logistic Regression Accuracy**: Achieves classification accuracy for binary classification using logistic regression.\n- **Lasso Regression Coefficients**: Highlights features with the strongest impact on petal length.\n\n## Conclusion\nThis project demonstrates effective data preprocessing, visualization, and machine learning applications using logistic and Lasso regression, providing insights into feature selection and binary classification within the Iris dataset.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsaadhaniftaj%2Flogistic--lasso-regression-data-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsaadhaniftaj%2Flogistic--lasso-regression-data-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsaadhaniftaj%2Flogistic--lasso-regression-data-analysis/lists"}