SVM stands for Support Vector Machine which is a well known artificial intelligence methodology to classified any objects based on a its multiple characteristics.
Like most artificial intelligence algorithms, SVM needs to be trained before-hand. My self developed algorithm is a Multiclass SVM that employs different kernels have proven to have high accuracy >90%.
The SVM kernels are Linear, Polynomial, Radial Basis Function (RBF) & Sigmoid. All of them might have different accuracy results depending on the type of the data that you want to classified with.
Obviously, please contact me first (to avoid cancellation) before buying this gig, as this gig will surely cost more than 1 GIG. You will need to buy the EXTRAs. You can also buy this gig if you have any questions for your own SVM projects for your thesis, projects, etc.