[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-117964-en":3,"doc-seo-117964-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},117964,3848291630094,"Emma Wilson","https://eur-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45",8,"Research & Report","Machine Learning-Based Assessment of Obesity - An Investigation of Model Performance and Feature Selection","This thesis applies multiple machine learning algorithms to assess obesity levels using eating habits and physical conditions. The work leverages obesity estimation data from the UCI Machine Learning Repository and systematically compares candidate models to identify the most robust approach for obesity estimation and prediction. In addition to predictive accuracy evaluation, the study determines the crucial features in the best-performing model, aiming to improve interpretability and reliability. Results support ongoing machine learning and healthcare efforts for obesity prediction.","UCLA  \nUCLA Electronic Theses and Dissertations  \nTitle  \nMachine Learning-Based Assessment of Obesity: An Investigation of Model Performance and Feature Selection  \nPermalink  \n[https://escholarship.org/uc/item/7qm5673z](https://escholarship.org/uc/item/7qm5673z)  \nAuthor  \nAslanpour, Dareh  \nPublication Date  \n2023  \nPeer reviewed|Thesis/dissertation  \n[eScholarship.org](eScholarship.org) Powered by the California Digital Library  \nUniversity of California  \nUNIVERSITY OF CALIFORNIA  \nLos Angeles  \nMachine Learning-Based Assessment of Obesity: An Investigation of Model Performance and Feature Selection  \nA thesis submitted in partial satisfaction of the requirements for the degree Master of Applied Statistics and Data Science  \nby  \nDareh Aslanpour  \n2023  \n➞ Copyright by Dareh Aslanpour 2023  \nABSTRACT OF THE THESIS  \nMachine Learning-Based Assessment of Obesity: An Investigation of Model Performance and Feature Selection  \nby  \nDareh Aslanpour  \nMaster of Applied Statistics and Data Science  \nUniversity of California, Los Angeles, 2023  \nProfessor Yingnian Wu, Chair  \nThe objective of this paper is to employ various machine learning algorithms to investigate the assessment of obesity levels based on eating habits and physical conditions. The study will utilize the obesity level estimation data provided by UCI Machine Learning Repository. The performance of different model candidates will be evaluated and compared in order to select the most robust model for obesity estimation or prediction. Moreover, this research aims to identify the crucial features used in the best predictive model to enhance the accuracy of obesity prediction. This study intends to contribute to the ongoing research in the field of machine learning and healthcare by providing insights into the prediction of obesity.  \nThe thesis of Dareh Aslanpour is approved.  \nMaryam Mahtash Esfandiari Frederic R Paik Schoenberg Yingnian Wu, Committee Chair  \nUniversity of California, Los Angeles 2023  \nTo my parents and my brother. . . who continually believe in me far more than I believe in myself  \niv  \nTABLE OF CONTENTS  \n1 Introduction .................................. 1  \n2 Exploratory Data Analysis ......................... 3  \n2.1 Data Set .................................. 3  \n2.2 Attributes of Data Set .......................... 4  \n2.3 Dependent Variables ........................... 5  \n2.4 Variable Exploration Methodology ................... 10  \n2.5 Key Findings ............................... 11  \n3 Methodology ................................. 18  \n3.1 Logistic Regression ............................ 18  \n3.2 Random Forest .............................. 20  \n3.3 Gradient Boosting ............................ 22  \n3.4 XGBoost .................................. 22  \n4 Model Analysis ................................ 23  \n4.1 Logistic Regression ............................ 25  \n4.2 Random Forest .............................. 29  \n4.3 Gradient Boosting ............................ 32  \n4.4 XGBoost .................................. 34  \n4.5 Model Comparison ............................ 36  \n5 Limitations and Conclusion ........................ 39  \n5.1 Limitations ................................ 39  \n5.2 Conclusion ................................. 40  \nReferences ..................................... 42  \nLIST OF FIGURES  \n2.1 Frequency of BMI Classifications .................... 6  \n2.2 Frequency of Not Obese and Obese ................... 7  \n2.3 Frequency of Not Obese and Obese After Misclassified Observation and Under 18 Removal .......................... 8  \n2.4 Boxplots of BMI with Respect to Obesity ................ 9  \n2.5 Histogram for the Distribution of BMI ................. 9  \n2.6 Barplot of Gender with Respect to Obesity ............... 11  \n2.7 Boxplots of BMI by Whether or Not Person Frequently Consumes High Caloric Food ............................ 13  \n2.8 Boxplots of BMI by Daily Calorie Consumption Monitoring ..... 14  \n2.9 Variable ","cbCaiu4rqaL548sB","https://ap.wps.com/l/cbCaiu4rqaL548sB","pdf",478079,1,53,"English","en",105,"# Introduction\n# Exploratory Data Analysis\n## Data Set\n## Attributes of Data Set\n## Dependent Variables\n## Variable Exploration Methodology\n## Key Findings\n# Methodology\n## Logistic Regression\n## Random Forest\n## Gradient Boosting\n## XGBoost\n# Model Analysis\n## Logistic Regression\n## Random Forest\n## Gradient Boosting\n## XGBoost\n## Model Comparison\n# Limitations and Conclusion\n## Limitations\n## Conclusion\n# References","[{\"question\":\"What is the main objective of the study?\",\"answer\":\"To assess obesity levels by applying various machine learning algorithms, comparing model performance to select a robust model for obesity estimation or prediction.\"},{\"question\":\"Which data source is used for the analysis?\",\"answer\":\"The study uses the obesity level estimation dataset from the UCI Machine Learning Repository.\"},{\"question\":\"How does the thesis improve obesity prediction beyond accuracy evaluation?\",\"answer\":\"It identifies crucial features used in the best predictive model to enhance the accuracy and interpretability of obesity predictions.\"}]","Machine Learning-Based Assessment of Obesity - An Investigation of Model Performance and Feature Selection | PDF",1785680556,134,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"machine-learning-based-assessment-of-obesity-an-investigation-of-model-performance-and-feature-selection","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/machine-learning-based-assessment-of-obesity-an-investigation-of-model-performance-and-feature-selection/117964/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-02",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What is the main objective of the study?","Question",{"text":75,"@type":76},"To assess obesity levels by applying various machine learning algorithms, comparing model performance to select a robust model for obesity estimation or prediction.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which data source is used for the analysis?",{"text":80,"@type":76},"The study uses the obesity level estimation dataset from the UCI Machine Learning Repository.",{"name":82,"@type":73,"acceptedAnswer":83},"How does the thesis improve obesity prediction beyond accuracy evaluation?",{"text":84,"@type":76},"It identifies crucial features used in the best predictive model to enhance the accuracy and interpretability of obesity predictions.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]