Type of neural network
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Dylan den Hartog
2021 年 8 月 2 日
編集済み: Vignesh Murugavel
2021 年 8 月 4 日
I am starting to work with neural networks. I am wondering what kind of neural network this is? Is is an Artificical Neural Network, a Convolutional Neural Network, or a Recurrent Neural Network? I generated this code with the Neural Pattern Recognition app.
% Solve a Pattern Recognition Problem with a Neural Network
% Script generated by Neural Pattern Recognition app
% Created 29-Jul-2021 10:43:09
% This script assumes these variables are defined:
% wineInputs - input data.
% wineTargets - target data.
x = wineInputs;
t = wineTargets;
% Choose a Training Function
% For a list of all training functions type: help nntrain
% 'trainlm' is usually fastest.
% 'trainbr' takes longer but may be better for challenging problems.
% 'trainscg' uses less memory. Suitable in low memory situations.
trainFcn = 'trainscg'; % Scaled conjugate gradient backpropagation.
% Create a Pattern Recognition Network
hiddenLayerSize = 10;
net = patternnet(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,t);
% Test the Network
y = net(x);
e = gsubtract(t,y);
performance = perform(net,t,y)
tind = vec2ind(t);
yind = vec2ind(y);
percentErrors = sum(tind ~= yind)/numel(tind);
% View the Network
view(net)
% Plots
% Uncomment these lines to enable various plots.
%figure, plotperform(tr)
%figure, plottrainstate(tr)
%figure, ploterrhist(e)
%figure, plotconfusion(t,y)
%figure, plotroc(t,y)
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Vignesh Murugavel
2021 年 8 月 4 日
編集済み: Vignesh Murugavel
2021 年 8 月 4 日
Pattern recognition networks are feedforward networks that can be trained to classify inputs according to target classes
Refer Link: https://www.mathworks.com/help/deeplearning/ref/patternnet.html
A feedforward neural network is an artificial neural network wherein connections between the nodes do not form a cycle.As such, it is different from its descendant: recurrent neural network (check wiki)
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