MapReduce fuzzy C-means ensemble clustering with soft AdaBoost for large data analytics
Abstract
Big data clustering is an important procedure used in a variety of application sectors. Existing clustering methods are incapable of dealing with enormous amounts of data, resulting in a greater false positive rate. The MapReduce gradient descent gentle AdaBoost clustering (MGDGAC) approach is developed to cluster such huge datasets with more accuracy. The MGDGAC approach is used to create MapReduce fuzzy C-means (MFCM) clustering, in which a big dataset is initially segmented into a number of chunks that are then processed in parallel on separate nodes to successfully accomplish clustering procedures in a short amount of time. Mappers are used to arrange data with higher membership values into clusters. The reducer in MFCM clustering then re-estimates the centroid value and iteratively feeds it to the mapper until it reaches a specific iteration and groups.
References
Gupta, K., & Jiwani, N. (2021). A systematic Overview of Fundamentals and Methods of Business Intelligence. International Journal of Sustainable Development in Computing Science, 3(3), 31-46. Retrieved from https://www.ijsdcs.com/index.php/ijsdcs/article/view/118
Momen, Mohammad Abdul. "FPGA-Based Acceleration of Expectation Maximization Algorithm using High Level Synthesis." MASc Thesis, University of Windsor, 2017.
Yixing Li, Zichuan Liu, Kai Xu, Hao Yu, and Fengbo Ren. 2018. A GPU Outperforming FPGA Accelerator Architecture for Binary Convolutional Neural Networks. J. Emerg. Technol. Comput. Syst. 14, 2, Article 18 (July 2018), 16 pages.
Kaiyuan Guo, Shulin Zeng, Jincheng Yu, Yu Wang, and Huazhong Yang. 2019. [DL] A Survey of FPGA-based Neural Network Inference Accelerators. ACM Trans. Reconfigurable Technol. Syst. 12, 1, Article 2 (March 2019), 26 pages.
Pawan Whig and S. N. Ahmad, On the Performance of ISFET-based Device for Water Quality Monitoring. Int'l J. of Communications, Network and System Sciences (IJCNS) (Nov 2011) ISSN (ONLINE): 1913-3715, ISSN (PRINT):1913-3723, Vol 4 pp: 709-719.
Pawan Whig and S. N. Ahmad, DVCC based Readout Circuitry for Water Quality Monitoring System, International Journal of Computer Applications (IJCA) ISBN : 973-93-80869-71-6,Volume 49 pp: 1-7.
Pawan Whig and S. N. Ahmad, A CMOS Integrated CC-ISFET Device for Water Quality Monitoring, International Journal of Computer Science Issues ,Volume 9, Issue 4, July 2012, ISSN (online): 1694-0814 pp: 365-371.
Pawan Whig and S. N. Ahmad, Performance Analysis of Various Readout Circuits for Monitoring Quality of Water Using Analog Integrated Circuits, International Journal of Intelligent Systems and Applications (IJISA) ISSN: 2074-904X (Print), ISSN: 2074-9058 (Online) Volume 4, No.11, October 2012 pp:91-98.
