[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-121075-en":3,"doc-seo-121075-105":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},121075,8796095462418,"Noah","https://ap-avatar.wpscdn.com/avatar/80000253c1241d02b47?x-image-process=image/resize,m_fixed,w_180,h_180&k=1778826106357471780",8,"Research & Report","Predictive Analysis of Local House Prices - Leveraging Machine Learning for Real Estate Valuation","This paper examines the real estate market potential in the urban settings of Frisco and Plano, Texas. By integrating traditional real estate analysis with machine learning, it builds predictive models to forecast home prices and evaluate investment feasibility. The study emphasizes continual model refinement using updated data to improve forecasting accuracy over time. Investors can use the outputs to spot high-growth areas, optimize decisions, and capitalize on emerging trends and investment hotspots.","SMU Data Science Review  \n\n| Volume 8\u003Cbr>Number 1 Spring 2024 | Article 12 |\n| --- | --- |\n| Predictive Analysis of Local House Prices: Leveraging Machine Learning for Real Estate Valuation\u003Cbr>Joey Hernandez\u003Cbr>Southern Methodist University, [joeyvhernandez@gmail.com](joeyvhernandez@gmail.com)\u003Cbr>Danny Chang\u003Cbr>Southern Methodist University, [changd@smu.edu](changd@smu.edu)\u003Cbr>Santiago Gutierrez\u003Cbr>Southern Methodist University, [gutierrezs@smu.edu](gutierrezs@smu.edu)\u003Cbr>Paul Huggins\u003Cbr>[paul.huggins@lanternstudios.com](paul.huggins@lanternstudios.com)\u003Cbr>Follow this and additional works at: [https://scholar.smu.edu/datasciencereview](https://scholar.smu.edu/datasciencereview)\u003Cbr> Part of the Data Science Commons, and the Real Estate Commons |  |\n\nRecommended Citation  \nHernandez, Joey; Chang, Danny; Gutierrez, Santiago; and Huggins, Paul () \"Predictive Analysis of Local House Prices: Leveraging Machine Learning for Real Estate Valuation,\" SMU Data Science Review: Vol. 8: No. 1, Article 12.  \nAvailable at: [https://scholar.smu.edu/datasciencereview/vol8/iss1/12](https://scholar.smu.edu/datasciencereview/vol8/iss1/12)  \nThis Article is brought to you for free and open access by SMU Scholar. It has been accepted for inclusion in SMU Data Science Review by an authorized administrator of SMU Scholar. For more information, please visit [http://digitalrepository.smu.edu](http://digitalrepository.smu.edu).  \nPredictive Analysis of Local House Prices: Leveraging  \nMachine Learning for Real Estate Valuation  \nSantiago Gutiérrez, Daniel Chang, Joey Hernandez, Paul Huggins  \nMaster of Science in Data Science, Southern Methodist University,  \nDallas, TX 75205 USA [gutierrezs@smu.edu](gutierrezs@smu.edu), [changd@smu.edu](changd@smu.edu),  [joeyhernandez@smu.edu](joeyhernandez@smu.edu)   \nAbstract: This paper presents a comprehensive study examining the real estate  \nmarket potential in the dynamic urban landscapes of Frisco and Plano, Texas.  \nCombining traditional real estate analysis with cutting-edge machine learning  \ntechniques, the study aims to predict home prices and assess investment  \nfeasibility. Leveraging these findings, the study proposes a strategic focus on  \npredictive modeling and investment potential identification, emphasizing the  \ncontinual refinement of machine learning models with updated data to accurately  \nforecast changes in the real estate market. By harnessing the predictive power of  \nthese models, investors can identify high-growth areas and optimize their  \ninvestment decisions, thus capitalizing on emerging trends and investment  \nhotspots in Frisco and Plano. This study highlights the potential of advanced  \nanalytical tools in guiding investors toward lucrative real estate opportunities in  \nrapidly developing urban environments.  \n1 Introduction  \nReal estate investment, recognized for its potential in wealth generation and economic  \ngrowth, remains a domain historically perceived as exclusive and often inaccessible  \n(Ullah & Sepasgozar, 2020) . Prevailing misconceptions have deterred individuals,  \nparticularly those from modest backgrounds, from considering it a viable investment  \noption (Ullah & Sepasgozar, 2020) . This exclusivity is compounded by the challenge  \nof obtaining real-time data, an essential component for informed investment decisions,  \npotentially leaving investors navigating the market without clear and comprehensive  \ninsights (Ullah & Sepasgozar, 2020) .  \nThis research addresses complexities inherent in-home valuation within the residential real estate sector. Its primary aim is to simplify and make accessible the  \nprocess of property valuation for investment purposes, fostering inclusivity and  \nunderstanding in this domain. By concentrating on residential real estate valuation, the  \nstudy presents a focused entry point for aspiring investors, guiding them in the accurate  \nvaluation of homes. A significant aspect of this research is the application of machine  \nlearning t","cbCaisWvhI8FoAoW","https://ap.wps.com/l/cbCaisWvhI8FoAoW","pdf",1102383,1,29,"English","en",105,"# Abstract\n# 1 Introduction\n# Real Estate Investment Context\n## In-Home Valuation Challenges\n## Democratization Through Technology and AI\n# Research Focus on Plano and Frisco, Texas\n## Predicting House Prices and Rental Yields\n## Investment Opportunities and Model Use","[{\"question\":\"What market areas does the study focus on?\",\"answer\":\"The study focuses on Frisco and Plano, Texas, which are described as growing urban areas with increasing population and development.\"},{\"question\":\"How does the research use machine learning?\",\"answer\":\"Machine learning techniques are used to predict home prices and to assess investment feasibility, supporting data-driven property valuation and decision-making.\"},{\"question\":\"What is the main goal of the predictive modeling approach?\",\"answer\":\"The approach aims to simplify and make property valuation accessible for investment purposes, while continually refining models with updated data to forecast market changes more accurately.\"}]","Predictive Analysis of Local House Prices - Leveraging Machine Learning for Real Estate Valuation | PDF",1785733595,73,{"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},"predictive-analysis-of-local-house-prices-leveraging-machine-learning-for-real-estate-valuation","",{"@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/predictive-analysis-of-local-house-prices-leveraging-machine-learning-for-real-estate-valuation/121075/",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":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What market areas does the study focus on?","Question",{"text":75,"@type":76},"The study focuses on Frisco and Plano, Texas, which are described as growing urban areas with increasing population and development.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the research use machine learning?",{"text":80,"@type":76},"Machine learning techniques are used to predict home prices and to assess investment feasibility, supporting data-driven property valuation and decision-making.",{"name":82,"@type":73,"acceptedAnswer":83},"What is the main goal of the predictive modeling approach?",{"text":84,"@type":76},"The approach aims to simplify and make property valuation accessible for investment purposes, while continually refining models with updated data to forecast market changes more accurately.","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"]