Method and apparatus for finding the best splits in a decision tree for a language model for a speech recognizer
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United States of America Patent
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Nov 16, 1993
Grant Date -
N/A
app pub date -
Oct 26, 1989
filing date -
Oct 26, 1989
priority date (Note) -
Expired
status (Latency Note)
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Abstract
A method and apparatus for finding the best or near best binary classification of a set of observed events, according to a predictor feature X so as to minimize the uncertainty in the value of a category feature Y. Each feature has three or more possible values. First, the predictor feature value and the category feature value of each event is measured. The events are then split, arbitrarily, into two sets of predictor feature values. From the two sets of predictor feature values, an optimum pair of sets of category feature values is found having the lowest uncertainty in the value of the predictor feature. From the two optimum sets of category feature values, an optimum pair of sets is found having the lowest uncertainty in the value of the category feature. An event is then classified according to whether its predictor feature value is a member of a set of optimal predictor feature values.
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