Example from patternnet docs fails in Neural Network Toolbox Version 10.0 (R2017a)
조회 수: 2 (최근 30일)
이전 댓글 표시
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)
댓글 수: 2
Walter Roberson
2017년 9월 17일
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.
채택된 답변
Greg Heath
2017년 9월 17일
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
댓글 수: 2
Greg Heath
2017년 9월 17일
P.S.
Any one interested in calculating the correlation coefficient between the 100 samples of NMSE and PCTERR?
추가 답변 (1개)
Greg Heath
2017년 9월 17일
편집: Greg Heath
2017년 9월 17일
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
댓글 수: 0
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