Best classification algorithm for microarrays and -omics data sets

Question

[bbmisraccb]

For microarrays and -omics data sets (where, samples <<< genes/proteins) out of several classification algorithms, which is efficient?

So, out of existing classification algorithms such as Support Vector Machine (SVM), K-nearest neighbor (KNN), Interval Valued Classification (IVC) and the improvised Interval Value based Particle Swarm Optimization (IVPSO) algorithm which one is potentially robust in handling, reliable in terms of results (not necessarily popular!) and why?