Creating ensembles of decision trees through sampling
Abstract
A system for decision tree ensembles that includes a module to read the data, a module to sort the data, a module to evaluate a potential split of the data according to some criterion using a random sample of the data, a module to split the data, and a module to combine multiple decision trees in ensembles. The decision tree method is based on statistical sampling techniques and includes the steps of reading the data; sorting the data; evaluating a potential split according to some criterion using a random sample of the data, splitting the data, and combining multiple decision trees in ensembles.
- Inventors:
- Issue Date:
- Research Org.:
- Univ. of California, Oakland, CA (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1175481
- Patent Number(s):
- 6938049
- Application Number:
- 10/167,892
- Assignee:
- The Regents of the University of California (Oakland, CA)
- Patent Classifications (CPCs):
-
G - PHYSICS G06 - COMPUTING G06N - COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
Y - NEW / CROSS SECTIONAL TECHNOLOGIES Y10 - TECHNICAL SUBJECTS COVERED BY FORMER USPC Y10S - TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- DOE Contract Number:
- W-7405-ENG-48
- Resource Type:
- Patent
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 97 MATHEMATICS AND COMPUTING
Citation Formats
Kamath, Chandrika, and Cantu-Paz, Erick. Creating ensembles of decision trees through sampling. United States: N. p., 2005.
Web.
Kamath, Chandrika, & Cantu-Paz, Erick. Creating ensembles of decision trees through sampling. United States.
Kamath, Chandrika, and Cantu-Paz, Erick. Tue .
"Creating ensembles of decision trees through sampling". United States. https://www.osti.gov/servlets/purl/1175481.
@article{osti_1175481,
title = {Creating ensembles of decision trees through sampling},
author = {Kamath, Chandrika and Cantu-Paz, Erick},
abstractNote = {A system for decision tree ensembles that includes a module to read the data, a module to sort the data, a module to evaluate a potential split of the data according to some criterion using a random sample of the data, a module to split the data, and a module to combine multiple decision trees in ensembles. The decision tree method is based on statistical sampling techniques and includes the steps of reading the data; sorting the data; evaluating a potential split according to some criterion using a random sample of the data, splitting the data, and combining multiple decision trees in ensembles.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Aug 30 00:00:00 EDT 2005},
month = {Tue Aug 30 00:00:00 EDT 2005}
}
Save to My Library
You must Sign In or Create an Account in order to save documents to your library.