Binary Classification with patternnet - wrong output
5 Ansichten (letzte 30 Tage)
Ältere Kommentare anzeigen
Hi together,
what i want to do, is to train a neural network (patternnet) classificator. Inputs are the size 10000x7, so 10.000 samples and 7 inputs.
Output is logical (10.000x1).
My problem is, if i use the patternnet function with a HiddenLayerSize > [], my output is no longer binary, than in a range between [0,1].
Here is my code:
hiddenLayerSize = [10,10,10];
net = patternnet(hiddenLayerSize, method);
net = configure(net, in_train', out_train');
net.input.processFcns = {'removeconstantrows','mapminmax'};
net.output.processFcns = {'removeconstantrows','mapminmax'};
net.trainParam.goal = gl;
net.divideFcn = divider; % Divide data randomly
net.divideMode = divMod; % Divide up every sample
net.divideParam.trainRatio = x/100;
net.divideParam.valRatio = y/100;
net.divideParam.testRatio = z/100;
net.performFcn = pfFcn;
net.trainParam.epochs = epoch;
net.Layers{:}.transferFcn = transfer;
net = train(net,in_train',out_train'
What can i do?
Thanks :)
0 Kommentare
Antworten (1)
Anshika Chaurasia
am 28 Sep. 2020
Hello Vincent,
It is my understanding that after training the neural network, the ouput is in range between [0,1] and you want output as logical i.e., {0,1}.
For getting logical output you could apply threshold i.e., if output >= 0.5 then output = 1 or else output = 0.
% Train the Network
[net,tr] = train(net,inputs,targets);
% Test the Network
outputs = net(inputs);
logical_output = zeros(1,10000);
logical_output(outputs >= 0.5) = 1; % applying threshold
1 Kommentar
Siehe auch
Kategorien
Mehr zu Sequence and Numeric Feature Data Workflows finden Sie in Help Center und File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!