Data classification methodology and pattern analysis for knowledge discovery and data mining
by Attili Venkata Ramana; Annaluri Sreenivasa Rao; Somula Ramasubbareddy
International Journal of Digital Enterprise Technology (IJDET), Vol. 2, No. 1, 2022

Abstract: Excess usage of information with the help of big data (BD) applications, the society of computer sciences needs to adopt various online classification tools and different types of pattern reorganisation (PR) techniques. The data collected from different types of sensor networks (SN), online patterns, images, etc. are the different sources of big data and to deal with such data, natural processing (NP) and data mining (DM) techniques are not capable of facing the challenges to deal with huge amount of data. To deal with such type of challenges, in this research a new algorithm is proposed based on DM and knowledge discovery (KD) using the network entropy (NE). Initially, the needful data is introduced using support vector machine (SVM), neural networks (NN) and decision trees (DT) methods. In the later stages, using machine learning (ML) techniques and pattern theory an organisational structure of network graphical pattern is constructed. From different databases, the simulation results obtained from the proposed approach shows good effectiveness and feasibility.

Online publication date: Mon, 22-Aug-2022

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