Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/157358
Title: Housing price prediction using deep learning
Authors: Song, Yutong
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Song, Y. (2022). Housing price prediction using deep learning. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/157358
Abstract: Housing price forecasting is critical in assisting both developers and consumers in maximizing their advantages. In this research, the performance of deep learning approaches will be compared to that of other machine learning algorithms in predicting the housing resale price index in Singapore and the United States. Data inputs contain both historical housing resale prices and potential macroeconomic indicators. Fundamental and technical analysis will be conducted to evaluate different machine learning models. Throughout the study, we will compare and contrast multiple models, the Long Short-Term Memory, Recurrent Neural Network, Gated Recurrent Unit, Multi-Layer Perceptron, Support Vector Regressor, and Gradient Boosting Regressor.
URI: https://hdl.handle.net/10356/157358
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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