{"id":26224879,"url":"https://github.com/oguzhantekeli06/datascience_machinelearning_prediction","last_synced_at":"2026-04-25T10:36:47.024Z","repository":{"id":258823855,"uuid":"864651698","full_name":"OguzhanTekeli06/DataScience_MachineLearning_Prediction","owner":"OguzhanTekeli06","description":"Data science project ","archived":false,"fork":false,"pushed_at":"2024-12-18T16:11:17.000Z","size":30,"stargazers_count":0,"open_issues_count":2,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-12-26T21:59:46.960Z","etag":null,"topics":["data-visualization","datascience-machinelearning","numpy","python3"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/OguzhanTekeli06.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":"2024-09-28T19:39:11.000Z","updated_at":"2024-12-18T16:11:20.000Z","dependencies_parsed_at":"2024-10-26T08:48:51.292Z","dependency_job_id":"5425e31d-b991-4707-bc02-781e51b200ac","html_url":"https://github.com/OguzhanTekeli06/DataScience_MachineLearning_Prediction","commit_stats":null,"previous_names":["oguzhantekeli06/assignments_repo","oguzhantekeli06/datascience_machinelearning_prediction"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/OguzhanTekeli06/DataScience_MachineLearning_Prediction","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/OguzhanTekeli06%2FDataScience_MachineLearning_Prediction","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/OguzhanTekeli06%2FDataScience_MachineLearning_Prediction/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/OguzhanTekeli06%2FDataScience_MachineLearning_Prediction/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/OguzhanTekeli06%2FDataScience_MachineLearning_Prediction/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/OguzhanTekeli06","download_url":"https://codeload.github.com/OguzhanTekeli06/DataScience_MachineLearning_Prediction/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/OguzhanTekeli06%2FDataScience_MachineLearning_Prediction/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32259472,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-25T09:15:33.318Z","status":"ssl_error","status_checked_at":"2026-04-25T09:15:31.997Z","response_time":59,"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-visualization","datascience-machinelearning","numpy","python3"],"created_at":"2025-03-12T18:28:31.467Z","updated_at":"2026-04-25T10:36:47.005Z","avatar_url":"https://github.com/OguzhanTekeli06.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Audio Features Mood Classification\nThis project demonstrates how to build a machine learning model to predict mood based on audio features. Using audio data (valence, energy, danceability, etc.), a Random Forest Classifier is trained to classify moods, and feature importance is visualized.\n\n## Project Structure\ndata_processing.py: Handles loading and preprocessing the JSON data.\nmodel.py: Contains model training and evaluation functions.\nvisualization.py: Visualizes feature importance.\n\nHow to Use\n\nLoad Data\nfrom data_processing import load_data_from_json\nX_train, X_test, y_train, y_test = load_data_from_json('data/audio_feature_with_mood.json')\n\n\nTrain Model\nfrom model import train_model\nclf = train_model(X_train, y_train)\n\n\nEvaluate Model\nfrom model import evaluate_model\nevaluate_model(clf, X_test, y_test)\n\n\nVisualize Feature Importance\nfrom visualization import plot_feature_importance\nplot_feature_importance(clf)\n\n## Dependencies\nInstall the required Python libraries:\n\npip install pandas numpy scikit-learn matplotlib\n\n**File Descriptions**\ndata_processing.py: Loads and preprocesses audio feature data from a JSON file.\nmodel.py: Contains functions for training and evaluating the Random Forest Classifier.\nvisualization.py: Visualizes the importance of features used by the classifier.\n\n## Future Work\nImproving model accuracy by experimenting with other classifiers.\nAdding more features and tuning hyperparameters.\n\n## License\nThis project is licensed under the MIT License.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Foguzhantekeli06%2Fdatascience_machinelearning_prediction","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Foguzhantekeli06%2Fdatascience_machinelearning_prediction","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Foguzhantekeli06%2Fdatascience_machinelearning_prediction/lists"}