Oct 13, 2012 � The IAMC method firstly constructs two collections of classifiers: one utilizes the descriptive attributes only while the other is augmented�...

Apr 1, 2013 � Iterative classification for multiple target attributes. Guo, Hongyu; L�tourneau, Sylvain https://publications-cnrc.canada.ca/fra/droits. L�...

This paper introduces a novel solution. Our approach employs an iterative classification strategy to exploit the relationships among multiple target attributes�...

This paper introduces a novel solution. Our approach employs an iterative classification strategy to exploit the relationships among multiple target attributes�...

Neville, J., & Jensen, D. (2000). Iterative classification in relational data. In AAAI workshop on learning statistical models from relational data (pp. 13-20).

Multiple classifiers are learned on independent sets of attributes, from the all the available training data. Each classifier is run and its most confidently.

Jul 8, 2017 � No they are not same, rather two inter-related concepts but have major difference. Actually multi-label classification is derived from multi-target.

We employ the predictive clustering approach to learn rules for simultaneous prediction of multiple target attributes. We propose a new rule learning algorithm,�...

the iterative procedure for prediction of multiple object types by simply combining the results of multiple classifiers. Each classifier would make use of�...

In network theory, collective classification is the simultaneous prediction of the labels for multiple objects