Patent ID: 7231376

Claim:
A method for identifying a support vector machine (SVM) to facilitate classification of a set of life science data, comprising: receiving a training dataset comprised of a number of data vectors; setting an initial SVM to be a current SVM; iteratively performing: determining to what extent each data vector violates conditions associated with the current SVM; sorting the data vectors based on each data vector's degree of violation; partitioning the sorted data vectors into a number of prioritized subsets, wherein the subset with the highest priority contains the largest number of violators with the highest degree of violation; solving in parallel a quadratic problem (QP) optimization problem for each subset based on the subset's priority; and constructing a new SVM to replace the current SVM based on the QP optimization solution for each subset; wherein the new SVM becomes current SVM, and wherein solving the QP optimization problem for each subset based on the subset's priority involves formulating an objective function for the QP optimization problem, and wherein the objective function includes interaction terms which are based on subsets whose priority is lower than the present subset's priority; discontinuing the iterative operations when conditions associated with the current SVM are met; and producing the current SVM as the final SVM which can facilitate classification of the set of life science data.