{"id":22445394,"url":"https://github.com/anas436/patient-class-and-drug-prediction-using-decision-tree-with-python","last_synced_at":"2026-04-10T01:07:47.879Z","repository":{"id":110394511,"uuid":"532323609","full_name":"Anas436/Patient-Class-and-Drug-Prediction-Using-Decision-Tree-with-Python","owner":"Anas436","description":null,"archived":false,"fork":false,"pushed_at":"2022-09-03T17:08:50.000Z","size":26,"stargazers_count":0,"open_issues_count":0,"forks_count":1,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-02-01T15:30:34.471Z","etag":null,"topics":["decision-tree-classifier","matplotlib","numpy","pandas","python3","scikit-learn","sklearn","sklearn-metrics","train-test-split"],"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/Anas436.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":"2022-09-03T17:06:46.000Z","updated_at":"2022-09-03T17:11:33.000Z","dependencies_parsed_at":null,"dependency_job_id":"d7395509-83e7-40e4-aa90-081d094ddd50","html_url":"https://github.com/Anas436/Patient-Class-and-Drug-Prediction-Using-Decision-Tree-with-Python","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/Anas436%2FPatient-Class-and-Drug-Prediction-Using-Decision-Tree-with-Python","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Anas436%2FPatient-Class-and-Drug-Prediction-Using-Decision-Tree-with-Python/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Anas436%2FPatient-Class-and-Drug-Prediction-Using-Decision-Tree-with-Python/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Anas436%2FPatient-Class-and-Drug-Prediction-Using-Decision-Tree-with-Python/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Anas436","download_url":"https://codeload.github.com/Anas436/Patient-Class-and-Drug-Prediction-Using-Decision-Tree-with-Python/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245832680,"owners_count":20679701,"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":["decision-tree-classifier","matplotlib","numpy","pandas","python3","scikit-learn","sklearn","sklearn-metrics","train-test-split"],"created_at":"2024-12-06T03:14:07.777Z","updated_at":"2025-12-30T23:22:55.925Z","avatar_url":"https://github.com/Anas436.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Patient-Class-and-Drug-Prediction-Using-Decision-Tree-with-Python\n\n\n\n## Objectives\n\nAfter completing this lab you will be able to:\n\n*   Develop a classification model using Decision Tree Algorithm\n\n\nIn this lab exercise, you will learn a popular machine learning algorithm, Decision Trees. You will use this classification algorithm to build a model from the historical data of patients, and their response to different medications. Then you will use the trained decision tree to predict the class of an unknown patient, or to find a proper drug for a new patient.\n\n\n\u003ch1\u003eTable of contents\u003c/h1\u003e\n\n\u003cdiv class=\"alert alert-block alert-info\" style=\"margin-top: 20px\"\u003e\n    \u003col\u003e\n        \u003cli\u003e\u003ca href=\"https://#about_dataset\"\u003eAbout the dataset\u003c/a\u003e\u003c/li\u003e\n        \u003cli\u003e\u003ca href=\"https://#downloading_data\"\u003eDownloading the Data\u003c/a\u003e\u003c/li\u003e\n        \u003cli\u003e\u003ca href=\"https://#pre-processing\"\u003ePre-processing\u003c/a\u003e\u003c/li\u003e\n        \u003cli\u003e\u003ca href=\"https://#setting_up_tree\"\u003eSetting up the Decision Tree\u003c/a\u003e\u003c/li\u003e\n        \u003cli\u003e\u003ca href=\"https://#modeling\"\u003eModeling\u003c/a\u003e\u003c/li\u003e\n        \u003cli\u003e\u003ca href=\"https://#prediction\"\u003ePrediction\u003c/a\u003e\u003c/li\u003e\n        \u003cli\u003e\u003ca href=\"https://#evaluation\"\u003eEvaluation\u003c/a\u003e\u003c/li\u003e\n        \u003cli\u003e\u003ca href=\"https://#visualization\"\u003eVisualization\u003c/a\u003e\u003c/li\u003e\n    \u003c/ol\u003e\n\u003c/div\u003e\n\u003cbr\u003e\n\u003chr\u003e\n\n\n\u003cdiv id=\"about_dataset\"\u003e\n    \u003ch2\u003eAbout the dataset\u003c/h2\u003e\n    Imagine that you are a medical researcher compiling data for a study. You have collected data about a set of patients, all of whom suffered from the same illness. During their course of treatment, each patient responded to one of 5 medications, Drug A, Drug B, Drug c, Drug x and y. \n    \u003cbr\u003e\n    \u003cbr\u003e\n    Part of your job is to build a model to find out which drug might be appropriate for a future patient with the same illness. The features of this dataset are Age, Sex, Blood Pressure, and the Cholesterol of the patients, and the target is the drug that each patient responded to.\n    \u003cbr\u003e\n    \u003cbr\u003e\n    It is a sample of multiclass classifier, and you can use the training part of the dataset \n    to build a decision tree, and then use it to predict the class of an unknown patient, or to prescribe a drug to a new patient.\n\u003c/div\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fanas436%2Fpatient-class-and-drug-prediction-using-decision-tree-with-python","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fanas436%2Fpatient-class-and-drug-prediction-using-decision-tree-with-python","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fanas436%2Fpatient-class-and-drug-prediction-using-decision-tree-with-python/lists"}