{"id":20733432,"url":"https://github.com/moindalvs/assignment_decision_tree_1","last_synced_at":"2026-01-05T12:15:04.844Z","repository":{"id":127428337,"uuid":"498418056","full_name":"MoinDalvs/Assignment_Decision_Tree_1","owner":"MoinDalvs","description":null,"archived":false,"fork":false,"pushed_at":"2022-06-01T05:21:59.000Z","size":15738,"stargazers_count":3,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-28T00:45:33.447Z","etag":null,"topics":["cost-complexity-pruning","data-science","decision","decision-tree-classifier","hyper-parameter-optimization","hyperparameter-tuning","post-pruning","pruning-optimization"],"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/MoinDalvs.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":"2022-05-31T16:41:19.000Z","updated_at":"2023-05-01T02:45:04.000Z","dependencies_parsed_at":null,"dependency_job_id":"5b8cf00e-575e-4498-99fc-07ecb1b44dc5","html_url":"https://github.com/MoinDalvs/Assignment_Decision_Tree_1","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/MoinDalvs%2FAssignment_Decision_Tree_1","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MoinDalvs%2FAssignment_Decision_Tree_1/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MoinDalvs%2FAssignment_Decision_Tree_1/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MoinDalvs%2FAssignment_Decision_Tree_1/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/MoinDalvs","download_url":"https://codeload.github.com/MoinDalvs/Assignment_Decision_Tree_1/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245020316,"owners_count":20548158,"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":["cost-complexity-pruning","data-science","decision","decision-tree-classifier","hyper-parameter-optimization","hyperparameter-tuning","post-pruning","pruning-optimization"],"created_at":"2024-11-17T05:25:23.399Z","updated_at":"2026-01-05T12:15:04.817Z","avatar_url":"https://github.com/MoinDalvs.png","language":"Jupyter Notebook","readme":"# Decision Tree\n \nAssignment\n\n\nAbout the data: \nLet’s consider a Company dataset with around 10 variables and 400 records. \nThe attributes are as follows: \n- Sales -- Unit sales (in thousands) at each location\n- Competitor Price -- Price charged by competitor at each location\n- Income -- Community income level (in thousands of dollars)\n- Advertising -- Local advertising budget for company at each location (in thousands of dollars)\n- Population -- Population size in region (in thousands)\n- Price -- Price company charges for car seats at each site\n- Shelf Location at stores -- A factor with levels Bad, Good and Medium indicating the quality of the shelving location for the car seats at each site\n- Age -- Average age of the local population\n- Education -- Education level at each location\n- Urban -- A factor with levels No and Yes to indicate whether the store is in an urban or rural location\n- US -- A factor with levels No and Yes to indicate whether the store is in the US or not\n\nThe company dataset looks like this: \n \nProblem Statement:\nA cloth manufacturing company is interested to know about the segment or attributes causes high sale. \nApproach - A decision tree can be built with target variable Sale (we will first convert it in categorical variable) \u0026 all other variable will be independent in the analysis.\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmoindalvs%2Fassignment_decision_tree_1","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmoindalvs%2Fassignment_decision_tree_1","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmoindalvs%2Fassignment_decision_tree_1/lists"}