Title: Parallel progressive-based inductive subspace and fuzzy-based firefly algorithm for high ensemble data clustering

Authors: D. Karthika; K. Kalaiselvi

Addresses: Vels Institute of Science, Technology and Advanced Studies, Pallavaram, Chennai 117, India ' Vels Institute of Science, Technology and Advanced Studies, Pallavaram, Chennai 117, India

Abstract: Recently, the framework is proposed with techniques such as random subspace and constraint propagation for handling high dimensional data ensemble clustering. Huge dataset clustering is difficult for conventional sequential clustering methods since it requires higher computation time. Distributed parallel processing and methods are consequently useful towards attaining results and scalability constraints of clustering huge datasets. So, in this work, the parallel progressive-based inductive subspace ensemble clustering (PPISEC) algorithm is introduced with the concept of MapReduce (MR) to perform high dimensional data clustering. Depending on micro-clusters and correspondence relative, the clustering method is designed which is easily parallelised via MR and completed in moderately with a small number of MR rounds. However, in the PPISEC algorithm, the centroid values are selected with the help of an improved support vector machine (ISVM) classifier. Thus, the incremental ensemble member chosen (IEMC) progression is performed with fuzzy-based firefly algorithm (FFA), and the normalised cut algorithm is established to accomplish high dimensional data clustering. The outcome shows that, the proposed PPISEC framework, which performs well on three benchmark samples by utilising high dimensionality and enhanced the results than the conventional clustering ensemble approaches.

Keywords: clustering incremental ensemble member chosen; IEMC; improved support vector machine; ISVM; constraint propagation; CP; parallel progressive-based inductive subspace ensemble clustering; PPISEC; MapReduce; cluster ensemble; semi-supervised clustering; data mining.

DOI: 10.1504/IJCC.2023.130900

International Journal of Cloud Computing, 2023 Vol.12 No.2/3/4, pp.224 - 245

Received: 22 May 2020
Accepted: 01 Aug 2020
Published online: 14 May 2023 *

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