{"id":24912915,"url":"https://github.com/lkethridge/supervised_learning","last_synced_at":"2025-03-28T04:37:16.526Z","repository":{"id":273440890,"uuid":"919681975","full_name":"LKEthridge/Supervised_Learning","owner":"LKEthridge","description":"Supervised Learning project from TripleTen","archived":false,"fork":false,"pushed_at":"2025-01-20T22:51:21.000Z","size":332,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-02T05:28:58.616Z","etag":null,"topics":["class-imbalance-handling","confusion-matrix","data-upload","downsampling","f1-score","feature-prep","feature-scaling","fpr","imbalanced-classification","label-encoding","one-hot-encoding","ordinal-encoding","pr-curve","precision","recall","regression-metrics","roc-curve","supervised-learning","tpr","upsampling"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"cc0-1.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/LKEthridge.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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":"2025-01-20T20:11:31.000Z","updated_at":"2025-01-20T22:51:24.000Z","dependencies_parsed_at":"2025-01-20T23:37:26.472Z","dependency_job_id":null,"html_url":"https://github.com/LKEthridge/Supervised_Learning","commit_stats":null,"previous_names":["lkethridge/supervised_learning"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LKEthridge%2FSupervised_Learning","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LKEthridge%2FSupervised_Learning/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LKEthridge%2FSupervised_Learning/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LKEthridge%2FSupervised_Learning/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/LKEthridge","download_url":"https://codeload.github.com/LKEthridge/Supervised_Learning/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245972642,"owners_count":20702710,"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":["class-imbalance-handling","confusion-matrix","data-upload","downsampling","f1-score","feature-prep","feature-scaling","fpr","imbalanced-classification","label-encoding","one-hot-encoding","ordinal-encoding","pr-curve","precision","recall","regression-metrics","roc-curve","supervised-learning","tpr","upsampling"],"created_at":"2025-02-02T05:29:00.640Z","updated_at":"2025-03-28T04:37:16.480Z","avatar_url":"https://github.com/LKEthridge.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Supervised_Learning\n## *This was a Supervised Learning project for TripleTen. 👩🏽‍💻*\nThis project developed a Random Forest Classifier to predict customer churn for Beta Bank, achieving an F1 score of 0.61 and a strong AUC-ROC score despite class imbalance. By targeting likely-to-leave customers, the model provides a tool for optimizing retention strategies and aligning predictions with actual churn trends. This approach offers Beta Bank a data-driven solution to reduce customer attrition and secure its future.\n## Skills Highlighted\n👀 Supervised Learning\n🧼 Feature Prep including One-Hot, Label, and Ordinal Encoding\n⚖️ Feature Scaling \u0026 Class-Imbalance Handling\n🤔 Confusion Matrices, Precision, Recall, and F1 Score\n↕️ Imbalanced Classification with Upsampling or Downsampling\n🪨 ROC-Curve, PR Curve, True Positive Rate, and False Positive Rate\n💯 Regression Metrics\n## Installation \u0026 Usage\n* This project uses pandas, numpy, train_test_split, DecisionTreeClassifier, RandomForestClassifier, LogisticRegression, f1_score, roc_auc_score, accuracy_score, matplotlib.pyplot, shuffle, and StandardScaler.  It requires python 3.9.6.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flkethridge%2Fsupervised_learning","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flkethridge%2Fsupervised_learning","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flkethridge%2Fsupervised_learning/lists"}