Please use this identifier to cite or link to this item:
|Title:||A collaborative ability measurement for co-training|
|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)|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 9, 2017
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.