I wanted to implement machine learning algorithms (SVM and KNN) for a biometric-based authentication system to classify whether a user is genuine or not.
I have the feature data.
What I understood, in order for me to evaluate the performance of an algorithm using the equal error rate (EER), I have to obtain the score for each instance using a classification algorithm.
I have read about classification algorithm from books and papers. I couldn't find information on this.
Could you explain what is a classification score?
Could you suggest me any reading material for me to understand the concept?
By the way, I'm using MATLAB.
Best Answer
You can use some different metrics to measure the scores of your classification model.
Normally, we use a confusion matrix to determine the correct/incorrect evaluations, and use this information to calc the metrics. The true positive/true negative are the values your model predict correctly, and the false positive/negative are the opposite
The accuracy, for example, is the # of correct evaluations / # of cases, in other words, (TP+TN)/TP+TN+FP+FN
There are other metrics like precision, recall and F1.