Classification margins by resubstitution
M = resubMargin(obj)
Discriminant analysis classifier, produced using
Numeric column-vector of length
Estimate Resubstitution Margins for Discriminant Analysis Classifiers
Find the margins for a discriminant analysis classifier for Fisher's iris data by resubstitution. Examine several entries.
Load Fisher's iris data set.
Train a discriminant analysis classifier.
Mdl = fitcdiscr(meas,species);
Compute the resubstitution margins, and display several of them.
m = resubMargin(Mdl); m(1:25:end)
ans = 6×1 1.0000 1.0000 0.9998 0.9998 1.0000 0.9946
The classification margin is the difference between the classification score for the true class and maximal classification score for the false classes.
The classification margin is a column vector with the same number
of rows as in the matrix
X. A high value of margin
indicates a more reliable prediction than a low value.
For discriminant analysis, the score of a classification is the posterior probability of the classification. For the definition of posterior probability in discriminant analysis, see Posterior Probability.