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Topic: neural network
Replies: 3   Last Post: Jul 26, 2014 7:22 PM

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Greg Heath

Posts: 6,385
Registered: 12/7/04
Re: neural network
Posted: Jul 24, 2014 1:25 PM
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"Murugan Solaiyappan" wrote in message <lqor9e$g2s$1@newscl01ah.mathworks.com>...
> Dear matlab friends,
>
> Sorry friends. previous post is sent by incompletely.
>
> I want to predict the closing index of stock market. here is my data set,
>
> Input (1 to 4 column) and Target (5th column)
>
> open high low close
> 6033.12 6067.37 6032.62 6049.89
> 6008.59 6021.49 5935.59 5962.24
> 5947.6 5962.46 5875.2 5884.34
> 5912.29 5919.01 5833.02 5855.45
> 5845.02 5850.8 5794.54 5800.19
> 5800.92 5822.43 5706.75 5713.55
> 5698.31 5717.23 5630.83 5707.16
> 5737.99 5773.14 5635.84 5678.86
> 5700.84 5716.28 5596.4 5625.88
>
> research articles says that , open,high,low,close is treated as input and close is treated as target.
>
> My question is input contains 9 element and the target contains either from 1 to 9 or 2 to 9. or anything else.
>
> Please briefly explain to me regarding input and target pair for closing stock index prediction. I expect your answer as early as possible?


You forgot to list the target column

[ I N ] = size(input) % [ 4 9 ]
[ O N ] = size(target) % [ 1 9 ]

% Overfitting limit for hidden nodes

Hub = -1 + ceil( (N*O-O) / ( I + O + 1)) % 1

% N too low for validation stopping. So use regularization.
% Try training with noise added data and testing with original data
% Plot performance vs signal-to-noise ratio

help trainbr
doc trainbr

Hope this helps.

Greg



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