Description
[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:
per(i,1) false negative rate
= (false negatives)/(all output negatives)
per(i,2) false positive rate
= (false positives)/(all output positives)
per(i,3) true positive rate
= (true positives)/(all output positives)
per(i,4) true negative rate
= (true negatives)/(all output negatives) |
[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
|
[x,t] = simpleclass_dataset;
net = patternnet(10);
net = train(net,x,t);
y = net(x);
[c,cm,ind,per] = confusion(t,y)