I am trying to use the custom classfier VI included in the Vision Development Module in 2010. I classifying three different types of images A, B and C and have created different type of feature fectors for them using different momentums and image processing techniques. However, I am able to get a separtaion for the three classes but I find it very confusing the way the classifier is scored. I need to understand it so that I can compare the different feature vectors that I have created and pick the best one. I have tried SVM and Nearest Neighbor classifiers and I also want to compare their performance.
Using the IMAQ Classifier Accuracy VI I am able to get some scores out. But I would appreciate if someone could explain more deeply the theoretical meaning of these scores: