Input-Output Fitting problem with a Neural Network - Stock predication
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Hi, I'm trying to predict stock values(in this case, the closing value). In the end I want to achieve the same result as this example, Example
I will use the "close price" and its corresponding date, but I cannot figure out how to use "input" and "target" and what they mean.
% This script assumes these variables are defined:
x = simplefitInput; //
t = simplefitTargets;
% Create a Fitting Network
hiddenLayerSize = 10;
net = fitnet(hiddenLayerSize,trainFcn);
% setup Division of Data for Training, Validation, Testing
net.divideParam.trainRatio = 70/100;
net.divideParam.valRatio = 15/100;
net.divideParam.testRatio = 15/100;
% Train the Network
[net,tr] = train(net,x);
% Test the Network
y = net(x);
e = gsubtract(t,y);
performance = perform(net,t,y)
% View the Network
%view(net)
If understand it correctly, x is the input of the system. But what is t ? So Im wondering: What kind of values do I give to x and t ?
采纳的回答
Greg Heath
2014-6-5
close all, clear all, clc, plt = 0
% NOTE: SOME SEMICOLONS REMOVED FOR DISPLAY PURPOSES
% Read Useful Info
% help nndatasets
% doc nndatasets
% x is the input
% t is the training target for the output
% y is the output
% e is the error (e=t-y)
% Data Selection
[ x ,t ] = simplefit_dataset;
whos
[I N ] = size(x) %[ 1 94 ]
[O N ] = size(t) %[ 1 94 ]
%Read more Useful Info
% help simplefit_dataset
% doc simplefit_dataset
plt = plt+1, figure(plt)
plot(x,t,'LineWidth',2)
MSE00 = var(t',1) % 8.3378 MSE Reference
% Using as many defaults as is reasonable:
net = fitnet; % net = net will reveal all defaults
[ net tr y e] = train(net,x); % tr = tr will reveal training details
% y = net(x);
% e = t - y
MSE = mse(e) % 4.9880e-008 Mean-squared-error
NMSE = MSE/MSE00 % 5.9824e-009 Normalized
% Coefficient of determination, Rsquared, is interpreted as the fraction of target variance that is modeled by the net. See Wikipedia for a decent discussion
R2 = 1-NMSE % 1.0000 Almost Perfect!
%See the training record,tr, for details of the default data division into training, validation and test subsets and training details
tr = tr
Hope this helps.
Thank you for formally accepting my answer
Greg
更多回答（1 个）
Greg Heath
2014-6-5
编辑：Greg Heath
2014-6-5
My previous answer is for regression and curve-fitting.
Unfortunately, I concentrated more on your given code than your written description.
You have a time-series problem and should be using the time-series function NARXNET; not the regression/fitting function FITNET.
help narxnet
doc narxnet
For MATLAB time-series example data
help nndatasets
doc nndatasets
I have posted tens of examples. Search the NEWSGROUP and ANSWERS using
greg narxnet
and
greg narxnet nncorr
For your case the output target is probably close or adjusted close. The inputs are the other tabulations. Try searching for
narxnet stock
narxnet forecasting
Hope this helps.
Thank you for formally accepting my answer
Greg
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