Combining resilient classifiers
AssigneeMicrosoft Corporation
InventorsSrivatsan Laxman, Ramarathnam Venkatesan
Life of this patent
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Abstract
A classification system is described for resiliently classifying data. In various embodiments, the classification system constructs a combined classifier based on multiple classifiers that are constructed to classify a set of training data. The combined classifier can be constructed in parallel with the multiple classifiers and applied to classify data.
Claims20
A method performed by a computer system for combining multiple classifiers, comprising:
- for each classifier, setting to zero multipliers associated with data elements that were not used to construct the classifier;
- and
- constructing a combined classifier by setting its multiplier values to a weighted average of the multipliers associated with the multiple classifiers.
A system for combining multiple support vector machines, comprising:
- a component that computes at least two Lagrange multipliers, each Lagrange multiplier computed to construct a support vector machine based on a subset of original training data that is randomly selected from the original training data;
- and
- a combined support vector machine, the combined support vector machine computed based at least in part on an aspect of the support vector machines based on the subsets of original training data.
A computer-readable medium storing computer-executable instructions that, when executed, cause a computer system to perform a method for combining multiple support vector machines, the method comprising:
- receiving at least two support vector machines constructed from an original set of training data;
- creating a new training data set based on classifications provided by each of the at least two support vector machines for the original training data set from which the support vector machines were derived;
- and
- constructing a combined support vector machine based on the new training data set.
Dependencies are inferred from the claim text.