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How to load own data set into neural network?
I am fairly new to MATLAB and I would like help in understanding about datasets. For classification in neural network, the example for wine classification show:
[x,t] = wine_dataset;
net = patternnet(10);
I have a dataset of input [8×4]matrix and target [4×4]matrix. How do I input this into neural network such that I can use the function patternnet?
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Exactly as indicated in
x = yourinput;
t = yourtarget; % target columns should be unit vectors with a single 1
DOCUMENTATION BUG: the default input is (10,’trainscg’) NOT (20,’trainlm’)!
close all, clear all, clc
[ x, t ] = iris_dataset;
[ I N ] = size(x) % [ 4 150 ]
[ O N ] = size(t) % [ 3 150 ]
trueclass = vec2ind(t);
MSE00 = mean(var(t',1)) % 0.222 biased MSE for naive constant output model
MSE00a = mean(var(t',0)) % 0.224 unbiased MSE for naive constant output model
Ntrn = N - 2*(0.15*N) % 105 default size of training set
Ntrneq = Ntrn*O % 315 Number of training equations
% Nw = (I+1)*H+(H+1)*O % No. of unknown weights for H hidden nodes
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