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|Title:||Using a machine learning approach for property market analysis||Authors:||Xu, Mengxing||Keywords:||DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition||Issue Date:||2016||Abstract:||This report aims to predict the property market trend for Singapore and Hong Kong with Python and some packages including pandas and scikit-learn. A machine learning approach was applied to perform the predictions with three regression models selected. Raw data was collected from the region or country’s corresponding government website. Before performing the training and testing using regression models, the raw data went through data cleaning and preprocessing. In the end, the predictions with regression models were conducted. Linear regression fit the Hong Kong property market best, while the K-Nearest Neighbors with k equals 3 performs best in Singapore property market. However, the future trend for both markets cannot be obtained due to the lack of latest data for some macroeconomic factors.||URI:||http://hdl.handle.net/10356/67393||Rights:||Nanyang Technological University||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||SCSE Student Reports (FYP/IA/PA/PI)|
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