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ISSN 1004-9037
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Edited by: Editorial Board of Journal of Data Acquisition and Processing
P.O. Box 2704, Beijing 100190, P.R. China
Sponsored by: Institute of Computing Technology, CAS & China Computer Federation
Undertaken by: Institute of Computing Technology, CAS
Published by: SCIENCE PRESS, BEIJING, CHINA
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      09 May 2023, Volume 38 Issue 3
    Article

    ANALYSIS AND PREDICTION FOR STOCK MARKET WITH PHARAMA SECTOR USING DATA MINING AND MACHINE LEARNING APPROACHES
    1 M. Vijayakanth and 2 V. Veeramanikandan
    Journal of Data Acquisition and Processing, 2023, 38 (3): 771-785 . 

    Abstract

    The unpredictable nature of stock markets makes it hard to accurately predict the future. Nevertheless, there are countless individuals trying to enhance their chances of making a profit from their investments by developing a range of different models and methodologies. Despite being theoretically sound, most models and techniques don't work well in the real world due to their low hit rate. One of the primary reasons being the volatile nature of markets. Therefore, the focus of current research in the stock forecasting area is to improve the accuracy of stock trading forecasts. This paper introduces a system that addresses the particular need in the field of pharmaceutical stock market analysis using data mining and machine learning approaches. This system incorporates a range of data mining processes and helps to make informed decisions when it comes to pharmaceutical stock trades. This new system incorporates several machine learning algorithms, including the Gaussian Process, Linear Regression Model, Random Forest, Random Tree and Reduced Error Pruning Tree approaches to accurately predict the Pharmaceutical Stock Market Analysis in India. Its accuracy parameters include the Correlation Coefficient, MAE, RMSE, RAE and RRSE.

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