{"id":28379407,"url":"https://github.com/reusjimenez/bikebuyer-predictive-analysis","last_synced_at":"2026-04-28T17:34:15.151Z","repository":{"id":293686584,"uuid":"984501306","full_name":"ReusJimenez/bikebuyer-predictive-analysis","owner":"ReusJimenez","description":"Notebook con cinco modelos de clasificación para predecir la intención de compra de clientes. 🚴‍♂️📊","archived":false,"fork":false,"pushed_at":"2025-05-16T15:24:50.000Z","size":3645,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-05-30T02:44:38.284Z","etag":null,"topics":["bikebuyers","classification","data-science","machine-learning","python","supervised-learning"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","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/ReusJimenez.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,"zenodo":null}},"created_at":"2025-05-16T03:20:43.000Z","updated_at":"2025-05-16T15:25:31.000Z","dependencies_parsed_at":"2025-05-16T16:35:37.408Z","dependency_job_id":"412a5e7e-cf6e-4563-9113-5a92f6c07130","html_url":"https://github.com/ReusJimenez/bikebuyer-predictive-analysis","commit_stats":null,"previous_names":["reusjimenez/bikebuyer-predictive-analysis"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/ReusJimenez/bikebuyer-predictive-analysis","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ReusJimenez%2Fbikebuyer-predictive-analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ReusJimenez%2Fbikebuyer-predictive-analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ReusJimenez%2Fbikebuyer-predictive-analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ReusJimenez%2Fbikebuyer-predictive-analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ReusJimenez","download_url":"https://codeload.github.com/ReusJimenez/bikebuyer-predictive-analysis/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ReusJimenez%2Fbikebuyer-predictive-analysis/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32392298,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-28T14:34:11.604Z","status":"ssl_error","status_checked_at":"2026-04-28T14:32:37.009Z","response_time":56,"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":["bikebuyers","classification","data-science","machine-learning","python","supervised-learning"],"created_at":"2025-05-30T02:38:20.629Z","updated_at":"2026-04-28T17:34:15.145Z","avatar_url":"https://github.com/ReusJimenez.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 🚴‍♂️ Análisis Predictivo – Probabilidad de Compra (Dataset Bikebuyer)\n\nNotebook para predecir la intención de compra de clientes mediante cinco modelos de clasificación, con enfoque en segmentación.\n\n## 🎯 Objetivos\n\n- Documentar paso a paso en un notebook.\n- Aplicar el proceso SEMMA al dataset `bikebuyer`.\n- Realizar limpieza de datos, análisis exploratorio y entrenamiento de 5 modelos de machine learning.\n- Evaluar desempeño de los modelos de clasificación\n- Extraer conclusiones relevantes basadas en los resultados.\n\n## 📌 Acciones Principales\n\n- Carga y exploración inicial del dataset.\n- Análisis exploratorio de datos (EDA) con visualizaciones para variables clave como ingreso, hijos, autos y distancia de traslado.\n- Limpieza y transformación del dataset: manejo de valores nulos y eliminación de columnas irrelevantes.\n- Codificación de variables categóricas para preparar los datos para el modelado.\n- División del dataset en conjuntos de entrenamiento y prueba.\n- Entrenamiento de cinco modelos de clasificación: Árbol de Decisión, KNN, Gradient Boosting, Random Forest y Extra Trees.\n- Evaluación de modelos mediante F1-score, matriz de confusión y curva ROC-AUC.\n\n## ✅ Conclusiones\n\n- En términos de **exactitud** y **AUC-ROC**, el **Árbol de Decisión** mostró el mejor rendimiento global, seguido de cerca por el **KNN**, mientras que el **Gradient Boosting** tuvo un rendimiento sólido pero ligeramente inferior.\n- El **Árbol de Decisión** se destacó en la identificación de la clase 0 (compradores) y mostró la mejor **sensibilidad**. Sin embargo, el **Gradient Boosting** y **KNN** también demostraron capacidades fuertes en términos de **precisión** y **recall**.\n- En general, el **Árbol de Decisión** se posiciona como el modelo más robusto para este conjunto de datos, seguido por **KNN**, mientras que **Gradient Boosting**, aunque efectivo, podría beneficiarse de ajustes adicionales para mejorar la identificación de la clase positiva.\n\n## 📩 Contacto\n\nSi tienes alguna pregunta o sugerencia, contáctame por [LinkedIn](https://linkedin.com/in/roberto-eustaquio/)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Freusjimenez%2Fbikebuyer-predictive-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Freusjimenez%2Fbikebuyer-predictive-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Freusjimenez%2Fbikebuyer-predictive-analysis/lists"}