Regression model for appraisal of real estate using recurrent neural network and boosting tree
暂无分享,去创建一个
Gang Wang | Zheng Liu | Bryan Gardiner | Junchi Bin | Yihao Liu | Eric Li | Shi Yuan Tang | Shiyuan Tang | G. Wang | Yihao Liu | Zheng Liu | Bryan Gardiner | Eric Li | Junchi Bin
[1] Witold R. Rudnicki,et al. Boruta - A System for Feature Selection , 2010, Fundam. Informaticae.
[2] Antanas Verikas,et al. The mass appraisal of the real estate by computational intelligence , 2011, Appl. Soft Comput..
[3] J. Friedman. Greedy function approximation: A gradient boosting machine. , 2001 .
[4] Carlos Guestrin,et al. XGBoost : Reliable Large-scale Tree Boosting System , 2015 .
[5] Bernhard Sick,et al. Deep Learning for solar power forecasting — An approach using AutoEncoder and LSTM Neural Networks , 2016, 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC).
[6] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[7] Trevor Hastie,et al. The Elements of Statistical Learning , 2001 .
[8] K. Lam,et al. An Artificial Neural Network and Entropy Model for Residential Property Price Forecasting in Hong Kong , 2008 .
[9] Kai Chen,et al. A LSTM-based method for stock returns prediction: A case study of China stock market , 2015, 2015 IEEE International Conference on Big Data (Big Data).
[10] Witold R. Rudnicki,et al. Feature Selection with the Boruta Package , 2010 .