Mini Prince1,*, P. M. Joe Prathap2
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2789-2803, 2023, DOI:10.32604/iasc.2023.029533
- 17 August 2022
Abstract
In several fields like financial dealing, industry, business, medicine, et cetera, Big Data (BD) has been utilized extensively, which is nothing but a collection of a huge amount of data. However, it is highly complicated along with time-consuming to process a massive amount of data. Thus, to design the Distribution Preserving Framework for BD, a novel methodology has been proposed utilizing Manhattan Distance (MD)-centered Partition Around Medoid (MD–PAM) along with Conjugate Gradient Artificial Neural Network (CG-ANN), which undergoes various steps to reduce the complications of BD. Firstly, the data are processed in the pre-processing phase by
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