NDLI: Information Forests

Content Provider	IEEE Xplore Digital Library
Author	Zhao Yi Soatto, S. Dewan, M. Yiqiang Zhan
Copyright Year	2012
Description	Author affiliation: University of California, Los Angeles, USA (Zhao Yi; Soatto, S.) \|\| Siemens Medical Solutions, USA (Dewan, M.; Yiqiang Zhan)
Abstract	We describe Information Forests, an approach to classification that generalizes Random Forests by replacing the splitting criterion of non-leaf nodes from a discriminative one - based on the entropy of the label distribution - to a generative one - based on maximizing the information divergence between the class-conditional distributions in the resulting partitions. The basic idea consists of deferring classification until a measure of “classification confidence” is sufficiently high, and instead breaking down the data so as to maximize this measure. In an alternative interpretation, Information Forests attempt to partition the data into subsets that are “as informative as possible” for the purpose of the task, which is to classify the data. Classification confidence, or informative content of the subsets, is quantified by the Information Divergence. Our approach relates to active learning, semi-supervised learning, mixed generative/discriminative learning.
Starting Page	143
Ending Page	146
File Size	322440
Page Count	4
File Format	PDF
ISBN	9781467314732
e-ISBN	9781467314725
DOI	10.1109/ITA.2012.6181810
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-02-05
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Vegetation Entropy Silicon Indexes Decision trees Approximation methods
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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