Confident predictability: identifying reliable gene expression patterns for individualized tumor classification using a local minimax kernel algorithm.

Background: Molecular classification of tumors can be achieved by global gene expression profiling. Most machine learning classification algorithms furnish global error rates for the entire population. A few algorithms provide an estimate of probability of malignancy for each queried patient but the degree of accuracy of these estimates is unknown.