Open Access
CORRECTION
Correction: Stock Market Index Prediction Using Machine Learning and Deep Learning Techniques
1
Yangtze Delta Region Institute (Huzhou), University of Electronic Science and Technology of China, Huzhou, 313001, China
2
Abdul Wali Khan University Mardan, Mardan, 23200, Pakistan
3
School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731,
China
4
Brain Institute Peshawar, Peshawar, 25130, Pakistan
* Corresponding Authors: Amin ul Haq. Email: ; Rajesh Kumar. Email:
Intelligent Automation & Soft Computing 2023, 38(1), 107-107. https://doi.org/10.32604/iasc.2023.047463
Issue published 26 January 2024
This article is a correction of:
Stock Market Index Prediction Using Machine Learning and Deep Learning Techniques
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Abstract
This article has no abstract.In the article “Stock Market Index Prediction Using Machine Learning and Deep Learning Techniques” by Abdus Saboor, Arif Hussain, Bless Lord Y. Agbley, Amin ul Haq, Jian Ping Li and Rajesh Kumar, (Intelligent Automation & Soft Computing, 2023, Vol. 37, No. 2, pp. 1326–1344. doi: 10.32604/iasc.2023.038849), the Reference [8] was wrongly cited.
The authors sincerely apologize for any inconvenience caused by the inappropriate inclusion of Reference [8] and related content in the original text. The authors have corrected this mistake by removing Reference [8] and any related content referencing it in the main text.
Please find below the corrected information:
1. Deleted Reference [8]:
8. A. Ganser, B. Hollaus, and S. Stabinger “Classification of tennis shot with a neural network approach,” Sensors, vol. 21, no. 17, pp. 5703, 2021.
2. Deleted content referencing Reference [8] in the main text:
Radial Basis Function Network (RBF) is used by Ganser et al. [8] to predict NASDAQ and Shanghai indices where Locality Preserving Projections (LPP) were used for predictions. It was asserted that the suggested method performed accurately for either of the market indices.
The authors state that the scientific conclusions are unaffected. This correction was approved by the Intelligent Automation & Soft Computing Editorial Office. The original publication has also been updated.
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