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|Title:||A collaborative ability measurement for co-training||Authors:||Shen, D.
|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)||URI:||http://scholarbank.nus.edu.sg/handle/10635/40130||ISSN:||03029743|
|Appears in Collections:||Staff Publications|
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