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How to predict housing price using Neural Network Toolbox?

조회 수: 2 (최근 30일)
WT
WT 2014년 10월 10일
편집: WT 2014년 10월 10일
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

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Greg Heath
Greg Heath 2014년 10월 10일
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
  댓글 수: 2
Greg Heath
Greg Heath 2014년 10월 10일
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 2014년 10월 10일
편집: WT 2014년 10월 10일
Thank you for replying. Can i still use fitting tool with fitnet when the inputs are dependent on time?

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