This is the data I have now: 30 simple sequence repeat (SSR) markers for 80 cultivars of cucumber. 10 of the 80 cultivars belong to one cultivar (let's say A).
My goal is to classify an unknown cultivar into A or "not A" using tge 30 SSR markers.
I'm think of considering it as a classification problem (A vs non-A) and use machine learning method to build a model using the SSR markers as features. But the problem is that A cultivars don't have enough number of samples.
Do you have any suggestions which statistical method(s) I can try to solve this problem? Thanks in advance.