Example from patternnet docs fails in Neural Network Toolbox Version 10.0 (R2017a)
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I'd remove this post now if I could. Tracking down the function name conflict has been difficult. The code attached to this answer https://www.mathworks.com/matlabcentral/answers/100197-is-there-any-way-to-list-all-shadowed-files-in-the-matlab-path-in-matlab-7-8-2009a#answer_109545 got me started.
Original problem: Trying to run the example from
help paternnet
but get:
Index exceeds matrix dimensions.
Error in initnw>initialize_layer (line 168)
range(inputStart(j):inputStop(j),:) = temp2((inputStart(j):inputStop(j))-inputStart(j)+1,:);
Complete code (revised):
% NNTest from help patternnet
clear all
clc
dbstop if error
[x,t] = iris_dataset;
net = patternnet(10);
net = train(net,x,t);
Complete output:
Index exceeds matrix dimensions.
Error in initnw>initialize_layer (line 168)
range(inputStart(j):inputStop(j),:) = temp2((inputStart(j):inputStop(j))-inputStart(j)+1,:);
Error in initnw (line 93)
out1 = initialize_layer(in1,in2);
Error in initlay>initialize_network (line 147)
net = feval(initFcn,net,i);
Error in initlay (line 89)
out1 = initialize_network(in1);
Error in network/init (line 32)
net = feval(initFcn,net);
Error in network/configure (line 243)
net = init(net);
Error in nntraining.config (line 116)
net = configure(network(net),X,T);
Error in nntraining.setup>setupPerWorker (line 68)
[net,X,Xi,Ai,T,EW,Q,TS,err] = nntraining.config(net,X,Xi,Ai,T,EW,configNetEnable);
Error in nntraining.setup (line 43)
[net,data,tr,err] = setupPerWorker(net,trainFcn,X,Xi,Ai,T,EW,enableConfigure);
Error in network/train (line 335)
[net,data,tr,err] = nntraining.setup(net,net.trainFcn,X,Xi,Ai,T,EW,enableConfigure,isComposite);
Error in NNTest (line 7)
net = train(net,x,t);
Version information:
MATLAB Version: 9.2.0.556344 (R2017a)
Neural Network Toolbox Version 10.0 (R2017a)
OS info:
Mac OS X 10.11.6 (15G1611)
2 个评论
Walter Roberson
2017-9-17
The code
[x,t] = iris_dataset;
net = patternnet(10);
net = train(net,x,t);
view(net)
y = net(x);
perf = perform(net,t,y);
classes = vec2ind(y);
works for me in R2017a.
采纳的回答
Greg Heath
2017-9-17
clear all
clc
%stoperr
%Undefined function or variable 'stoperr'.
% [x,t] = iris_dataset;
% net = patternnet(10);
% net = train(net,x,t);
% view(net)
% y = net(x);
% perf = perform(net,t,y) %0.0302
% classes = vec2ind(y);
% end
% Error: Illegal use of reserved keyword "end".
close all, clear all, clc
[ x,t ] = iris_dataset;
[ I N ] = size(x)% [ 4 150 ]
[ O N ] = size(t)% [ 3 150]
truclass = vec2ind(t); % 1 to 3
MSEref = mse(t-mean(t,2)) % 0.2222
rng(0), Ntrials = 10
for h = 1:10 % No. of hidden nodes
net = patternnet(h);
for n = 1:Ntrials
net = configure(net,x,t);
[net tr y e ] = train(net,x,t);
% y = net(x); e = t-y;
NMSE(h,n) = mse(e)/MSEref;
predclass = vec2ind(y);
PCTERR(h,n) = 100*mean(predclass~=truclass);
end
end
PCTERR = PCTERR
% Columns 1 through 5
%
% 2.6667 2.0000 2.0000 3.3333 2.6667
% 2.0000 1.3333 2.6667 2.0000 2.0000
% 2.0000 2.0000 4.0000 0.6667 2.6667
% 1.3333 4.0000 4.0000 1.3333 1.3333
% 2.0000 3.3333 3.3333 2.6667 1.3333
% 3.3333 2.0000 2.6667 1.3333 2.0000
% 2.6667 4.6667 3.3333 4.0000 3.3333
% 1.3333 1.3333 2.6667 2.0000 4.6667
% 2.6667 0.6667 2.6667 1.3333 1.3333
% 2.0000 1.3333 1.3333 1.3333 4.0000
%
% Columns 6 through 10
%
% 3.3333 2.6667 2.0000 2.6667 2.0000
% 1.3333 68.6667 1.3333 2.6667 6.0000
% 1.3333 2.6667 2.6667 1.3333 1.3333
% 1.3333 3.3333 3.3333 4.0000 2.6667
% 3.3333 2.0000 1.3333 2.0000 1.3333
% 1.3333 1.3333 1.3333 2.6667 1.3333
% 2.0000 2.6667 2.6667 2.6667 1.3333
% 2.0000 1.3333 1.3333 2.0000 1.3333
% 3.3333 4.0000 3.3333 2.0000 2.0000
% 1.3333 1.3333 2.0000 2.6667 1.3333
Hope this helps,
Thank you for formally accepting my answer
Greg
2 个评论
Greg Heath
2017-9-17
P.S.
Any one interested in calculating the correlation coefficient between the 100 samples of NMSE and PCTERR?
更多回答(1 个)
Greg Heath
2017-9-17
编辑:Greg Heath
2017-9-17
I get two error messages:
clear all clc
%stoperr
%Undefined function or variable 'stoperr'.
[x,t] = iris_dataset;
net = patternnet(10);
net = train(net,x,t);
view(net)
y = net(x);
perf = perform(net,t,y);
classes = vec2ind(y);
% end
% Error: Illegal use of reserved keyword "end".
Hope this helps,
Greg
0 个评论
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