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  • E-ISSN:

    2454-9584

    P-ISSN

    2454-8111

    Impact Factor 2021

    5.610

    Impact Factor 2022

    6.247

  • E-ISSN:

    2454-9584

    P-ISSN

    2454-8111

    Impact Factor 2021

    5.610

    Impact Factor 2022

    6.247

  • E-ISSN:

    2454-9584

    P-ISSN

    2454-8111

    Impact Factor 2021

    5.610

    Impact Factor 2022

    6.247

INTERNATIONAL JOURNAL OF INVENTIONS IN ENGINEERING & SCIENCE TECHNOLOGY

International Peer Reviewed (Refereed), Open Access Research Journal
(By Aryavart International University, India)

Paper Details

EMPLOYABILITY OF A SMART MODEL BASED ON MACHINE LEARNING TOOLS AND TECHNIQUES IN THE ENHANCED FORECASTING OF STOCK PRICES

Suhasini Singh

Christ (deemed to be) University

141 - 148 Vol. 5, Jan-Dec, 2019
Receiving Date: 2019-10-03;    Acceptance Date: 2019-11-21;    Publication Date: 2019-12-02
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Abstract

Stock price prediction is a vital part of the monetary market. Forecasting the securities exchange effectively is essential to accomplish the greatest benefit. This paper focuses on applying AI algorithms like Random Forest, SVM, KNN and linear regression on datasets. We assess the algorithm by finding execution measurements like precision, Review, accuracy and f-score. We plan to distinguish the ideal calculation for predicting future financial exchange exhibitions. The fruitful forecast of the financial exchange will certainly affect the securities exchange structures and financial partners.

Keywords: Stock price prediction; monetary market; machine learning tools

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