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dc.rights.licenseAll rights reserveden_US
dc.contributor.advisorDuffany, Jeffrey
dc.contributor.authorDíaz Martínez, José E.
dc.date.accessioned2023-09-11T15:17:50Z
dc.date.available2023-09-11T15:17:50Z
dc.date.issued2023
dc.identifier.citationDíaz Martínez, J. E. (2023). Predicting the Housing Market with Machine Learning [Unpublished manuscript]. Graduate School, Polytechnic University of Puerto Rico.en_US
dc.identifier.urihttp://hdl.handle.net/20.500.12475/1940
dc.descriptionDesign Project Article for the Graduate Programs at Polytechnic University of Puerto Ricoen_US
dc.description.abstractThe aim of this project is to build a machine learning model for predicting housing market prices using a dataset that includes information about MSSubClass, MSZoning, LotArea, LotConfig, BldgType, OverallCond, YearBuilt, YearRemodAdd, BsmtFinSF2, TotalBsmtSF and Sale Price. The dataset will be analyzed using exploratory data analysis (EDA) techniques to identify patterns and correlations between the different features and the housing prices. Several machine learning algorithms will be used to build the predictive model, including linear regression, SVR, Random Forest Regression, and CatBooster. The performance of the model will be evaluated using mean squared error and techniques such as hyperparameter tuning will be used to optimize the model's performance. The final model will be used to provide insights and predictions for future investment based on the price of a property in 5 years [1]. Key Terms – Correlation, Exploratory Data Analysis, Sale Price, Support Vector Regression.en_US
dc.language.isoenen_US
dc.publisherPolytechnic University of Puerto Ricoen_US
dc.relation.ispartofComputer Science;
dc.relation.ispartofseriesSpring-2023;
dc.relation.haspartSan Juanen_US
dc.subject.lcshPolytechnic University of Puerto Rico--Graduate students--Researchen_US
dc.subject.lcshPolytechnic University of Puerto Rico--Graduate students--Postersen_US
dc.subject.lcshPolytechnic University of Puerto Rico--Subject headings--Unassigneden_US
dc.titlePredicting the Housing Market with Machine Learningen_US
dc.typeArticleen_US
dc.rights.holderPolytechnic University of Puerto Rico, Graduate Schoolen_US


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