Alternative to support vector machine classifier in python?
If your images that belong to the same class are results of a transformations to some starting image you can increase your training size by making transofrmations to your labeled examples. 
For example if you are doing character recognition, afine or elastic transforamtions can be used. P.Simard in  Best Practices for Convolutional Neural Networks Applied to Visual Document Analysis describes it in more detail. In the paper he uses Neural Networks but the same applies for SVM.
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 i need at least 100 images for class for using support vector machine , There is any alternative?