How to predict housing price using Neural Network Toolbox?

17 次查看(过去 30 天)
I would like to predict housing prices using inputs such as distance away from subway, numbers of rooms etc.. which of the 4 wizards ( fitting tool, pattern recognition tool, clustering tool, time series tool) should i use?
Thank You WT Lim

采纳的回答

Greg Heath
Greg Heath 2014-10-10
Use the fitting tool with fitnet
Also, see
help house_dataset
doc house_dataset
help fitnet
doc fitnet
[ x,t ] = house_dataset;
[ I N ] = size(x) % [ 13 506 ]
[ O N ] = size(t) % [ 1 506 ]
MSE00 = mean(var(t',1)) % 84.42
net = fitnet;
rng('default')
[net tr y e ] = train(net,x,t); % e=t-y
NMSE = mse(e)/MSE00 % normalized MSE = 0.071101
R2 = 1-NMSE % Rsquare (See Wikipedia) = 0.9289
% ~ 93% of the target variance is modeled by the net. % Obtain details from the training record
tr = tr
Hope this helps
Thank you for formally accepting my answer
Greg
  2 个评论
Greg Heath
Greg Heath 2014-10-10
Better solutions probably can be obtained by using
1. A different number of hidden nodes
2. A different set of random initial weigts
WT
WT 2014-10-10
编辑:WT 2014-10-10
Thank you for replying. Can i still use fitting tool with fitnet when the inputs are dependent on time?

请先登录,再进行评论。

更多回答(0 个)

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by