Functional link artificial neural network for multi-label classification

Document Type

Conference Article

Publication Title

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Abstract

In this article, a multi-label functional link artificial neural network (MLFLANN) has been developed to efficiently perform multi-label data classification. The input data is functionally expanded to a higher dimension, followed by iterative learning of the multi-label FLANN (MLFLANN) using the training set. The architecture of the network is less complex and the input space dimension is improved in an attempt to overcome the non-linear nature of the multi-label classification problem. The method has been validated on various multi-label datasets and the results are found to be encouraging.

First Page

1

Last Page

10

DOI

10.1007/978-3-319-71928-3_1

Publication Date

1-1-2017

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