An improved extreme learning machine to classify multinomial datasets using particle swarm optimisation

Abstract

Abstract:In this paper, we propose a particle swarm-based extreme learning machine (ELM) to classify datasets with varying number of classes. This work emphasises on a couple of important parameters, like maximisation of classification accuracy and minimisation of training time. As a machine classifier, an ELM has been chosen, which is an improvement over back propagation network. For each of the input dataset an optimised target was determined by using particle swarm optimisation (PSO) technique. Those specific targets are used with the input data to train the ELM during classification process. For this, some of the bench mark classification datasets are used. To compare the proposed method and some of the existing methods an extensive experimental study has been carried out; a comparative analysis is done by taking parameters like percentage of classification accuracy, training time and complexity of the computing algorithm.Keywords: multinomial classification; extreme learning machine; ELM; normalisation; particle swarm optimisation; PSO; back propagation neural network; classification; classification accuracy; input; target; complexity of algorithm.Reference to this paper should be made as follows: Dash, N., Priyadarshini, R. and Misra, R. (2017) 'An improved extreme learning machine to classify multinomial datasets using particle swarm optimisation', Int. J. Intelligent Systems Design and Computing, Vol. 1, Nos. 1/2, pp.127-144. Rachita Misra received her Doctoral degree from IIT Kharagpur, and is currently working as a Professor in the Department of IT, in C.V. Raman College of Engineering, Bhubaneswar. With more than 15 years of IT industry experience and 15 years of teaching and research experience, she has more than 30 publications in various reputed journals and conferences. Her areas of interest are digital image processing, data mining, soft computing, parallel computing, software engineering and project management. This paper is a revised and expanded version of a paper entitled 'An ANN Model to classify multinomial datasets with optimized target using particle swarm optimization technique' presented at