{"id":25203428,"url":"https://github.com/akimuddinshaikh/machine-learning-project","last_synced_at":"2026-05-16T18:05:41.673Z","repository":{"id":274385052,"uuid":"922735739","full_name":"Akimuddinshaikh/Machine-Learning-Project","owner":"Akimuddinshaikh","description":"A comparative study of regression models (Decision Tree, Random Forest, Ridge, Lasso, SVM) for predicting real estate prices in King County, NYC, and California using PCA \u0026 Pipeline techniques.","archived":false,"fork":false,"pushed_at":"2025-02-04T02:19:00.000Z","size":4661,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-04T22:43:23.341Z","etag":null,"topics":["machine-learning","pca-analysis","python","regression-models","scikit-learn","statsmodels"],"latest_commit_sha":null,"homepage":"","language":null,"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/Akimuddinshaikh.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":"2025-01-27T00:22:14.000Z","updated_at":"2025-02-04T02:20:08.000Z","dependencies_parsed_at":null,"dependency_job_id":"f49190f0-1608-4a88-9aff-7292143c28d9","html_url":"https://github.com/Akimuddinshaikh/Machine-Learning-Project","commit_stats":null,"previous_names":["akimuddinshaikh/machine-learning-project"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Akimuddinshaikh/Machine-Learning-Project","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Akimuddinshaikh%2FMachine-Learning-Project","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Akimuddinshaikh%2FMachine-Learning-Project/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Akimuddinshaikh%2FMachine-Learning-Project/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Akimuddinshaikh%2FMachine-Learning-Project/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Akimuddinshaikh","download_url":"https://codeload.github.com/Akimuddinshaikh/Machine-Learning-Project/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Akimuddinshaikh%2FMachine-Learning-Project/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":273069831,"owners_count":25040130,"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":"2025-09-01T02:00:09.058Z","response_time":120,"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":["machine-learning","pca-analysis","python","regression-models","scikit-learn","statsmodels"],"created_at":"2025-02-10T07:17:23.329Z","updated_at":"2026-05-16T18:05:41.647Z","avatar_url":"https://github.com/Akimuddinshaikh.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"Machine Learning Models for House Price Prediction\nA Comparative Study of Regression Models\n\n Author: Akimuddin Aslam Shaikh\n Institution: National College of Ireland, School of Computing\n\n\n **Project Overview**\nThis project explores various machine learning regression models to predict house prices based on real estate data from King County, NYC, and California. The study aims to compare the performance of different regression models and determine the most suitable approach for real estate price forecasting.\n\n **Key Highlights**\n✅ Implemented Decision Tree, Lasso, Linear, Random Forest, Ridge, and Support Vector Machine (SVM) Regression\n✅ Applied Pipeline module \u0026 PCA (Principal Component Analysis) for dimensionality reduction\n✅ Evaluated models using R-squared score, Mean Squared Error (MSE), and Root Mean Squared Error (RMSE)\n✅ Used StatsModel for regression analysis\n✅ Found that Random Forest Regression with PCA performed best for King County \u0026 California datasets, while NYC dataset yielded poor results across models\n\n\n**Technologies \u0026 Libraries Used**\nPython \nScikit-Learn (Regression models \u0026 PCA)\nStatsModels (Regression analysis)\nMatplotlib \u0026 Seaborn (Data visualization)\nPandas \u0026 NumPy (Data preprocessing)\n\n**Regression Models \u0026 Performance**\nModel\tR² Score\tMSE\tRMSE\tDataset\nRandom Forest + PCA\tBest\tLow\tLow\tKing County, California\nDecision Tree Regression\tModerate\tMedium\tMedium\tKing County, California\nLinear Regression\tModerate\tHigh\tHigh\tNYC\nSVM Regression\tPoor\tHigh\tHigh\tNYC\n **Key Finding:** The Random Forest Regression model with PCA performed best for King County \u0026 California datasets.\n **NYC Dataset:** None of the models achieved a positive R-squared score, highlighting dataset limitations.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fakimuddinshaikh%2Fmachine-learning-project","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fakimuddinshaikh%2Fmachine-learning-project","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fakimuddinshaikh%2Fmachine-learning-project/lists"}