how to calculate svm performance using different features what is the learning curve of scikit when do you test different feature vector what is the difference between a training set vs a svm? what is the difference between a feature vector and a svm does a learning curve affect the performance of a classifier is rbf a standard feature vector what is the svm distribution what's my pixel svm what is the difference between a training set and an svm different feature vectors for different features what is svm with different svms what classifiers have different feature vectors how many classes in svm what is the difference between a svm and an svm with different features? when using different training sets, feature vectors give what type of scores? how do svms differ how many different svms are in a training set what is the pixel range in svm what is the difference between a svm and a feature vector in a training set