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Functional Link Artificial Neural Network for Multi-label Classification

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10682)

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.

Keywords

Multi-label classification Neural networks Functional link artificial neural networks 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Machine Intelligence UnitIndian Statistical InstituteKolkataIndia
  2. 2.Department of Computer ScienceVidyasagar UniversityMedinipurIndia

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