[c,cm,ind,per] = confusion(targets,outputs) takes
these values:

targets

S-by-Q matrix,
where each column vector contains a single 1 value,
with all other elements 0. The index of the 1 indicates
which of S categories that vector represents.

outputs

S-by-Q matrix,
where each column contains values in the range [0,1].
The index of the largest element in the column indicates which of S categories
that vector represents.

and returns these values:

c

Confusion value = fraction of samples misclassified

cm

S-by-S confusion
matrix, where cm(i,j) is the number of samples
whose target is the ith class that was classified
as j

ind

S-by-S cell array,
where ind{i,j} contains the indices of samples
with the ith target class, but jth
output class

per

S-by-4 matrix,
where each row summarizes four percentages associated with the ith
class:

[c,cm,ind,per] = confusion(TARGETS,OUTPUTS) takes
these values:

targets

1-by-Q vector of
1/0 values representing membership

outputs

S-by-Q matrix,
of value in [0,1] interval, where values greater
than or equal to 0.5 indicate class membership

and returns these values:

c

Confusion value = fraction of samples misclassified

cm

2-by-2 confusion
matrix

ind

2-by-2 cell array,
where ind{i,j} contains the indices of samples
whose target is 1 versus 0,
and whose output was greater than or equal to 0.5 versus
less than 0.5

per

2-by-4 matrix where
each ith row represents the percentage of false
negatives, false positives, true positives, and true negatives for
the class and out-of-class

Examples

[x,t] = simpleclass_dataset;
net = patternnet(10);
net = train(net,x,t);
y = net(x);
[c,cm,ind,per] = confusion(t,y)