Patent ID: 6658395
Filing Date: 2003-12-02
Classification: G06K,G06N

Abstract:
A computer-implemented method for extracting information from large data sets using multiple support vector machines comprising:(a) receiving a training input comprising a plurality of training data sets containing a plurality of training data points of different data types; (b) pre-processing each of a first training data set comprising a first data type and a second training data set comprising a second data type to add dimensionality to each of the training data points within the first and second data sets; (c) training a first plurality of first-level support vector machines using the first pre-processed training data set, each first-level support vector machine of the first plurality comprising a plurality of different kernels selected from a first set of kernels; (d) training a second plurality of first-level support vector machines using the second pre-processed training data set, each first-level support vector machine of the second plurality comprising a second plurality of different kernels selected from a second set of kernels; (e) receiving test input comprising a plurality of test data sets containing a plurality of test data points of the different data types; (f) pre-processing each of a first test data set comprising the first data type and a second test data set comprising the second data type to add dimensionality to each of the test data points within the first and second test data sets; (g) testing each of the first plurality of trained first-level support vector machines using the first pre-processed test data set to generate a first plurality of test outputs; (h) testing each of the second plurality of trained first-level support vector machines using the second pre-processed test data set to generate a second plurality of test outputs; (i) identifying a first optimal solution, if any, from the first plurality of test outputs; (j) identifying a second optimal solution, if any, from the second plurality of test outputs; (k) combining the first optimal solution and the second optimal solution to create a second-level input data set to be input into each of a plurality of second-level support vector machines; (l) generating a second-level output for each second-level support vector machine; and (m) comparing the second-level outputs to identify and optimal second-level solution.