function EVAL = Evaluate(ACTUAL,PREDICTED)% This fucntion evaluates the performance of a classification model by
% calculating the common performance measures: Accuracy, Sensitivity,
% Specificity, Precision, Recall, F-Measure, G-mean.
% Input: ACTUAL = Column matrix with actual class labels of the training
% examples
% PREDICTED = Column matrix with predicted class labels by the
% classification model
% Output: EVAL = Row matrix with all the performance measures
idx = (ACTUAL()==1);p = length(ACTUAL(idx));n = length(ACTUAL(~idx));N = p+n;tp = sum(ACTUAL(idx)==PREDICTED(idx));tn = sum(ACTUAL(~idx)==PREDICTED(~idx));fp = n-tn;fn = p-tp;tp_rate = tp/p;tn_rate = tn/n;accuracy = (tp+tn)/N;sensitivity = tp_rate;specificity = tn_rate;precision = tp/(tp+fp);recall = sensitivity;f_measure = 2*((precision*recall)/(precision + recall));gmean = sqrt(tp_rate*tn_rate);EVAL = [accuracy sensitivity specificity precision recall f_measure gmean];
MATLAB: What is the value of predicted and actual
performance analysis
Best Answer