Discriminant forest classification method and system

Patent · Tue Nov 06 00:00:00 EST 2012

OSTI ID:1080437

Chen, Barry Y.; Hanley, William G.; Lemmond, Tracy D.; Hiller, Lawrence J.; Knapp, David A.; Mugge, Marshall J.

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.

• Research Organization: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC52-07NA27344
• Assignee: Lawrence Livermore National Security, LLC (Livermore, CA)
• Patent Number(s): 8,306,942
• Application Number: 12/436,667
• OSTI ID: 1080437
• Country of Publication: United States
• Language: English

Related Subjects

54 ENVIRONMENTAL SCIENCES