Applying Random Forests to Predict the Housing Price in Kaohsiung City
碩士 === 國立東華大學 === 財務金融學系 === 107 === This paper employs the popular machine learning algorithm "Random Forest" to build a housing price prediction model for Kaohsiung City using the Actual Price Registration data set. Decision tree could classify or predict target features with impressive...
Main Authors: | Zheng-Yu Li, 李政育 |
---|---|
Other Authors: | Jin-Lung Lin |
Format: | Others |
Language: | zh-TW |
Published: |
2019
|
Online Access: | http://ndltd.ncl.edu.tw/handle/q3mpbg |
Similar Items
-
An Empirical Study on The Housing Price in Kaohsiung City
by: Hsu, Wen-Yao, et al.
Published: (2017) -
A Study for the Housing Price by Applying Fuzzy Neural Network in Taipei and Kaohsiung Cities
by: Chih-hsun Chen, et al.
Published: (2008) -
The Effect of Green Park to Housing Price in Kaohsiung City
by: Huang, Chi-Yuan, et al.
Published: (2016) -
Analysis and prediction of second-hand house price based on random forest
by: Huang, J., et al.
Published: (2022) -
An Empirical Study on the Key Factors of the Housing Price in Kaohsiung City
by: Hsin-Hsien Chen, et al.
Published: (2014)