{"status":200,"statusText":"OK","data":{"uci_id":477,"name":"Real Estate Valuation","repository_url":"https://archive.ics.uci.edu/dataset/477/real+estate+valuation+data+set","data_url":"https://archive.ics.uci.edu/static/public/477/data.csv","abstract":"The real estate valuation is a regression problem. The market historical data set of real estate valuation are collected from Sindian Dist., New Taipei City, Taiwan. ","area":"Business","tasks":["Regression"],"characteristics":["Multivariate"],"num_instances":414,"num_features":6,"feature_types":["Integer","Real"],"demographics":[],"target_col":["Y house price of unit area"],"index_col":["No"],"has_missing_values":"no","missing_values_symbol":null,"year_of_dataset_creation":2018,"last_updated":"Mon Feb 26 2024","dataset_doi":"10.24432/C5J30W","creators":["I-Cheng Yeh"],"intro_paper":{"ID":373,"type":"NATIVE","title":"Building real estate valuation models with comparative approach through case-based reasoning","authors":"I. Yeh, Tzu-Kuang Hsu","venue":"Applied Soft Computing","year":2018,"journal":null,"DOI":null,"URL":"https://dl.acm.org/doi/abs/10.1016/j.asoc.2018.01.029","sha":null,"corpus":null,"arxiv":null,"mag":null,"acl":null,"pmid":null,"pmcid":null},"variables":[{"name":"No","role":"ID","type":"Integer","demographic":null,"description":null,"units":null,"missing_values":"no"},{"name":"X1 transaction date","role":"Feature","type":"Continuous","demographic":null,"description":"for example, 2013.250=2013 March, 2013.500=2013 June, etc.","units":null,"missing_values":"no"},{"name":"X2 house age","role":"Feature","type":"Continuous","demographic":null,"description":null,"units":"year","missing_values":"no"},{"name":"X3 distance to the nearest MRT station","role":"Feature","type":"Continuous","demographic":null,"description":null,"units":"meter","missing_values":"no"},{"name":"X4 number of convenience stores","role":"Feature","type":"Integer","demographic":null,"description":"number of convenience stores in the living circle on foot","units":"integer","missing_values":"no"},{"name":"X5 latitude","role":"Feature","type":"Continuous","demographic":null,"description":"geographic coordinate, latitude","units":"degree","missing_values":"no"},{"name":"X6 longitude","role":"Feature","type":"Continuous","demographic":null,"description":"geographic coordinate, longitude","units":"degree","missing_values":"no"},{"name":"Y house price of unit area","role":"Target","type":"Continuous","demographic":null,"description":"10000 New Taiwan Dollar/Ping, where Ping is a local unit, 1 Ping = 3.3 meter squared","units":"10000 New Taiwan Dollar/Ping","missing_values":"no"}],"additional_info":{"summary":"The market historical data set of real estate valuation are collected from Sindian Dist., New Taipei City, Taiwan. The “real estate valuation” is a regression problem. The data set was randomly split into the training data set (2/3 samples) and the testing data set (1/3 samples).","purpose":null,"funded_by":null,"instances_represent":null,"recommended_data_splits":null,"sensitive_data":null,"preprocessing_description":null,"variable_info":"The inputs are as follows\r\nX1=the transaction date (for example, 2013.250=2013 March, 2013.500=2013 June, etc.)\r\nX2=the house age (unit: year)\r\nX3=the distance to the nearest MRT station (unit: meter)\r\nX4=the number of convenience stores in the living circle on foot (integer)\r\nX5=the geographic coordinate, latitude. (unit: degree)\r\nX6=the geographic coordinate, longitude. (unit: degree)\r\n\r\nThe output is as follow\r\nY= house price of unit area (10000 New Taiwan Dollar/Ping, where Ping is a local unit, 1 Ping = 3.3 meter squared)\r\n","citation":null}}}