Selection of most effective machine learning kernel from a training set of documents
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United States of America Patent
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Feb 24, 2015
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N/A
app pub date -
Mar 15, 2012
filing date -
Mar 15, 2012
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Abstract
A server computing system selects a machine learning kernel from a plurality of machine learning kernels using a plurality of training documents. The server computing system identifies a plurality of testing documents from a plurality of electronic discovery documents based on the plurality of training documents. For each of the plurality of machine learning kernels and for each testing document in the plurality of testing documents, the server computing system determines a class of the testing document using a default value for each of a plurality of parameters for the machine learning kernel and evaluates a goodness of fit of the machine learning kernel for the testing document. The server computing system selects a machine learning kernel from the plurality of machine learning kernels and determines a value for at least one of the plurality of parameters for the selected machine learning kernel using a goodness of fit test.
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