Conditional maximum likelihood estimation of naïve bayes probability models
Number of patents in Portfolio can not be more than 2000
United States of America Patent
Stats
-
Nov 24, 2009
Grant Date -
Apr 6, 2006
app pub date -
Sep 15, 2004
filing date -
Sep 15, 2004
priority date (Note) -
In Force
status (Latency Note)
Importance
Abstract
A statistical classifier is constructed by estimating Naïve Bayes classifiers such that the conditional likelihood of class given word sequence is maximized. The classifier is constructed using a rational function growth transform implemented for Naïve Bayes classifiers. The estimation method tunes the model parameters jointly for all classes such that the classifier discriminates between the correct class and the incorrect ones for a given training sentence or utterance. Optional parameter smoothing and/or convergence speedup can be used to improve model performance. The classifier can be integrated into a speech utterance classification system or other natural language processing system.
First Claim
Family
International Classification(s)
Cited Art Landscape
Patent Citation Ranking
Advertisement
Advertisement
Advertisement
Recipient Email Address
Recipient Email Address
Comment
Recipient Email Address
Add to Portfolio(s)
To add this patent to one, or more, of your portfolios, simply click the add button.
This Patent is in these Portfolios:
Add to additional portfolios:
Last Refreshed On:
Changes done successfully