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Published in:
2021 | OriginalPaper | Chapter
A Novel Approach Based on Associative Rule Mining Technique for Multi-label Classification (ARM-MLC)
Authors : C. P. Prathibhamol, K. Ananthakrishnan, Neeraj Nandan, Abhijith Venugopal, Nandu Ravindran
Published in: Progress in Advanced Computing and Intelligent Engineering
Publisher: Springer Singapore
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Abstract
In this paper, we have implemented an efficient and novel technique for multi-label class prediction using associative rule mining. Many of the research works for the classification have been carried out on single-label datasets, but it is not useful for all real-world application accounting to multi-label datasets like scene classification, text categorization, etc. Hence, we propose an algorithm for performing multi-label classification and solve the problems which come across in the domain pertaining to single-label classification. Our novel technique (ARM-MLC) will aim in enhancing the accuracy of any decision-making processes. Here, in multi-label classification, based on our work, we aim to predict the multiple characters of the instances.