Performance Measures for Classification

This function evaluates the common performance measures for classification models.

Classification models in machine learning are evaluated for their performance by common performance measures. This function calculates the following performance measures: Accuracy, Sensitivity, Specificity, Precision, Recall, F-Measure and G-mean. The signature of the function and description of the arguments are given below:

EVAL = Evaluate(ACTUAL,PREDICTED)
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