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ISSN 2063-5346
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A STUDY ON DATA MINING APPROACHES FOR BANKING SHARE USING SUPERVISED MACHINE LEARNING APPROACHES

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M. Vijayakanth , V. Veeramanikandan
» doi: 10.31838/ecb/2023.12.1.570

Abstract

NIFTY, National Stock Exchange Fifty abbreviation, holds significant prominence within the Indian stock market. It is a pivotal benchmark index mirroring the performance of the top 50 most substantial and highly liquid corporations enlisted on India's National Stock Exchange (NSE). Data mining aims to convert unprocessed data into valuable and practical insights, assisting enterprises, researchers, and analysts in making knowledgeable choices and anticipating forthcoming trends. Supervised machine learning is a branch of artificial intelligence and machine learning where an algorithm learns from a labeled dataset. This approach provides the algorithm with input-output pairs, where the inputs are the features, and the outputs are the corresponding target values. This research considers overall banking share with five parameters processed using various supervised machine learning approaches and its accuracy parameters.

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