[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-119942-en":3,"doc-seo-119942-105":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":20,"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},119942,4398048949847,"Eliana","https://ap-avatar.wpscdn.com/avatar/400002536579ef2da7f?_k=1778318612642679267",8,"Research & Report","Performance comparison of machine learning algorithms - for predicting obesity level - Research article","Obesity has grown into a global health epidemic since 1980, creating serious repercussions for young adults, adults, and children. To support early detection, data mining and machine learning methods are applied to obesity forecasting. The study uses the Obesity Level dataset from the UCI Machine Learning Repository, containing 638 patients and 17 attributes. Nine ML algorithms are compared, and Logistic Regression achieves the best overall performance with accuracy, sensitivity, specificity, and AUC of 100% and 1.","RESEARCH ARTICLE | JUNE 28 2023  \nPerformance comparison of machine learning algorithms for predicting obesity level 􀀈  \nSuwarno 􀀧 ; Nerru Pranuta Murnaka; Puguh Wahyu Prasetyo; Samsul Arifin  \nAIP Conference Proceedings 2733, 020002 (2023)  \n[https://doi.org/10.1063/5.0140856](https://doi.org/10.1063/5.0140856)  \n􀀭  \nView Online  \n􀀱  \nExport Citation  \nCrossMark  \n06 August 2023 09:56:06  \nPerformance Comparison of Machine Learning Algorithms  \nfor Predicting Obesity Level  \nSuwarno 1,a), Nerru Pranuta Murnaka2,b), Puguh Wahyu Prasetyo3,c), Samsul  \nArifin4,d)  \n1Primary Teacher Education Department, Faculty of Humanities, Bina Nusantara University, Jakarta, Indonesia.  \n2Mathematics Education Department, STKIP Surya, Tangerang, Indonesia.  \n3Mathematics Education Department, Faculty of Teacher Training and Education, Universitas Ahmad Dahlan,  \nIndonesia.  \n4Statistics Department, School of Computer Science, Bina Nusantara University, Jakarta, 11480, Indonesia  \na)Corresponding author: [suwarno001@binus.ac.id](suwarno001@binus.ac.id)  \nb) [murnaka@gmail.com](murnaka@gmail.com)  \nc)[puguh.prasetyo@pmat.uad.ac.id](puguh.prasetyo@pmat.uad.ac.id)  \nd)[samsul.arifin@binus.edu](samsul.arifin@binus.edu)  \nAbstract. Obesity problems have actually come to be a worldwide epidemic that has increased since 1980, with significant repercussions for health and wellness in young adults, adults, and youngsters. Obesity problems are an issue that has actually been expanding steadily which is why daily appear new studies entailing youngsters' excessive weight, specifically those looking for influence elements as well as exactly how to predict the appearance of the condition under these elements;  \nfor this reason, early detection is called for. Data mining and also machine learning (ML) algorithms approaches are made use of in obesity problems forecast in our research. We made use of the Obesity Level dataset for our study, accumulated from the UCI Machine Learning Repository. The dataset includes information about 638 patients as well as their matching  \n17 attributes. We made use of nine ML algorithms on the dataset to predict obesity problems. We found that the model with Logistic Regression algorithm is well on obesity level prediction. The result validated Logistic Regression algorithm has the best performance of accuracy (100%), sensitivity (100%), specificity (100%), as well as AUC (1) . The Logistic Regression model was selected because to its best performance, best gain, and fastest total time.  \nINTRODUCTION  \nObesity is defined as having an excessive quantity of body fat. Weight gain is not just due to food intake; genetics and the environment can all play a role in the development of obesity. Because it is a worldwide health problem, it has the potential to pose a threat to the world in the future. Obesity can be caused by a variety of factors, and it can even be classified as a disease. Obesity is associated with thousands of dangers and illnesses in a variety of sectors. It is one of the most frequent health disorders in the globe, affecting people all over. Obesity is mostly caused by excessive eating combined with insufficient physical activity. If people do not burn off their excess energy by physical activities such as yoga, workouts, and fasting, but instead consume large quantities of energy, particularly fat and sugar, a significant portion of the excess energy is converted to fat and stored in the body as body fat. The majority of individuals are unconcerned with their weight since they believe it is one of the broad definitions of health. Furthermore, they believe that it will have no negative impact on their health. The outside structure of their body is all that is seen of them. However, the unpleasant reality is that obesity is a risk factor for the majority of illnesses. Occasionally, it can result in mortality, as seen by severe epidemics of diabetes, cardiovascular disease, cancer, osteoarthritis, chronic renal dis","cbCaipfET1F5Gq5b","https://ap.wps.com/l/cbCaipfET1F5Gq5b","pdf",918294,1,13,"English","en",105,"# Abstract\n# Introduction\n## Definition and contributing factors of obesity\n## Trends and public health impact\n## Related research and existing tools\n# Methods and data (from study description)\n## Dataset and features\n## Compared ML algorithms","[{\"question\":\"What dataset and inputs are used to predict obesity level?\",\"answer\":\"The study uses the Obesity Level dataset from the UCI Machine Learning Repository, including 638 patients with 17 attributes.\"},{\"question\":\"Which machine learning algorithm performs best for obesity level prediction?\",\"answer\":\"Logistic Regression shows the best performance, achieving accuracy 100%, sensitivity 100%, specificity 100%, and AUC 1.\"},{\"question\":\"Why is early detection emphasized in obesity prediction research?\",\"answer\":\"Because obesity has steadily increased and can lead to serious diseases and even mortality, early detection helps address the condition before severe outcomes occur.\"}]","Performance comparison of machine learning algorithms - for predicting obesity level - Research article | PDF",1785727118,33,{"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},"performance-comparison-of-machine-learning-algorithms-for-predicting-obesity-level-research-article","",{"@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/performance-comparison-of-machine-learning-algorithms-for-predicting-obesity-level-research-article/119942/",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","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What dataset and inputs are used to predict obesity level?","Question",{"text":75,"@type":76},"The study uses the Obesity Level dataset from the UCI Machine Learning Repository, including 638 patients with 17 attributes.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which machine learning algorithm performs best for obesity level prediction?",{"text":80,"@type":76},"Logistic Regression shows the best performance, achieving accuracy 100%, sensitivity 100%, specificity 100%, and AUC 1.",{"name":82,"@type":73,"acceptedAnswer":83},"Why is early detection emphasized in obesity prediction research?",{"text":84,"@type":76},"Because obesity has steadily increased and can lead to serious diseases and even mortality, early detection helps address the condition before severe outcomes occur.","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"]