These instances, whenmapped to an N-dimensional space, represent a core set that can be used to construct an approximation to theminimumenclosing ball. Solving the SVMlearning problem on these core sets can produce a good approximation solution i

It contains positional PID algorithm, integral separate PID, Including the least squares method, the SVM, neural networks, 1 _k neighbor method, Is a good learning materials to learn PCA feature extraction.