Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/40130
Title: A collaborative ability measurement for co-training
Authors: Shen, D.
Zhang, J.
Su, J.
Zhou, G.
Tan, C.-L. 
Issue Date: 2005
Source: 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)
URI: http://scholarbank.nus.edu.sg/handle/10635/40130
ISSN: 03029743
Appears in Collections:Staff Publications

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