Alternative to support vector machine? I have to make comparison between 155 image feature vectors. Every feature vector has got  5 features.
My image are divided in 10 classes.
Unfortunately for using support vector machine i need at least 100 images for class, There is any alternative?
Why not just stick with something simpler like k-nearest neighbors or (learning) vector quantization (PDF)?