The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Nov. 06, 2012
Filed:
May. 06, 2009
Barry Y. Chen, San Ramon, CA (US);
William G. Hanley, Livermore, CA (US);
Tracy D. Lemmond, Tracy, CA (US);
Lawrence J. Hiller, Livermore, CA (US);
David A. Knapp, Livermore, CA (US);
Marshall J. Mugge, Westerly, RI (US);
Barry Y. Chen, San Ramon, CA (US);
William G. Hanley, Livermore, CA (US);
Tracy D. Lemmond, Tracy, CA (US);
Lawrence J. Hiller, Livermore, CA (US);
David A. Knapp, Livermore, CA (US);
Marshall J. Mugge, Westerly, RI (US);
Lawrence Livermore National Security, LLC, Livermore, CA (US);
Abstract
A hybrid machine learning methodology and system for classification that combines classical random forest (RF) methodology with discriminant analysis (DA) techniques to provide enhanced classification capability. A DA technique which uses feature measurements of an object to predict its class membership, such as linear discriminant analysis (LDA) or Andersen-Bahadur linear discriminant technique (AB), is used to split the data at each node in each of its classification trees to train and grow the trees and the forest. When training is finished, a set of n DA-based decision trees of a discriminant forest is produced for use in predicting the classification of new samples of unknown class.