Please use this identifier to cite or link to this item:
Title: A collaborative ability measurement for co-training
Authors: Shen, D.
Zhang, J.
Su, J.
Zhou, G.
Tan, C.-L. 
Issue Date: 2005
Citation: Shen, D.,Zhang, J.,Su, J.,Zhou, G.,Tan, C.-L. (2005). A collaborative ability measurement for co-training. Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) 3248 : 436-445. ScholarBank@NUS Repository.
Abstract: This paper explores collaborative ability of co-training algorithm. We propose a new measurement (CA) for representing the collaborative ability of co-training classifiers based on the overlapping proportion between certain and uncertain instances. The CA measurement indicates whether two classifiers can co-train effectively. We make theoretical analysis for CA values in co-training with independent feature split, with random feature split and without feature split. The experiments justify our analysis. We also explore two variations of the general co-training algorithm and analyze them using the CA measurement. © Springer-Verlag Berlin Heidelberg 2005.
Source Title: Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
ISSN: 03029743
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

checked on May 22, 2019

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.