Predict resubstitution response of classifier
label = resubPredict(obj)
[label,posterior] = resubPredict(obj)
[label,posterior,cost] = resubPredict(obj)
Discriminant analysis classifier, produced using ClassificationDiscriminant.fit.
Response obj predicts for the training data. label is the same data type as the training response data obj.Y. The predicted class labels are those with minimal expected misclassification cost; see How the predict Method Classifies.
N-by-K matrix of posterior probabilities for classes obj predicts, where N is the number of observations and K is the number of classes.
N-by-K matrix of predicted misclassification costs. Each cost is the average misclassification cost with respect to the posterior probability.
posterior(i,k) is the posterior probability of class k for observation i. For the mathematical definition, see Posterior Probability.
Find the total number of misclassifications of the Fisher iris data for a discriminant analysis classifier:
load fisheriris obj = ClassificationDiscriminant.fit(meas,species); Ypredict = resubPredict(obj); % the predictions Ysame = strcmp(Ypredict,species); % true when == sum(~Ysame) % how many are different? ans = 3