An Ensemble of Random Forest Gradient Boosting Machine and Deep Learning Methods for Stock Price Prediction Journal Article

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MLA

Shrivastav, Lokesh Kumar, and Ravinder Kumar. "An Ensemble of Random Forest Gradient Boosting Machine and Deep Learning Methods for Stock Price Prediction." JITR vol.15, no.1 2022: pp.1-19. http://doi.org/10.4018/JITR.2022010102

APA

Shrivastav, L. K. & Kumar, R. (2022). An Ensemble of Random Forest Gradient Boosting Machine and Deep Learning Methods for Stock Price Prediction. Journal of Information Technology Research (JITR), 15(1), 1-19. http://doi.org/10.4018/JITR.2022010102

Chicago

Shrivastav, Lokesh Kumar, and Ravinder Kumar. "An Ensemble of Random Forest Gradient Boosting Machine and Deep Learning Methods for Stock Price Prediction," Journal of Information Technology Research (JITR) 15, no.1: 1-19. http://doi.org/10.4018/JITR.2022010102

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An Ensemble of Random Forest Gradient Boosting Machine and Deep Learning Methods for Stock Price Prediction

Journal of Information Technology Research (JITR)

The Journal of Information Technology Research (JITR) presents comprehensive interdisciplinary and refereed research on the most emerging and breakthrough areas of information science and technology. The journal seeks to improve and expand existing research in underrepresented areas of information science and technology in all areas of global implication. Through the current trends in the globalization of technology in the knowledge society, JITR will serve to provide the highest in quality concepts, methodologies, trends and case studies for all audiences.

The journal focuses on major breakthroughs within the technological arena, with particular concentration on the accelerating principles, concepts and applications of biocomputing, medical informatics, anthropocentric computing, high-performance computing, technological diffusion, predictive analysis tools, genetic algorithms, and cultural informatics. This scholarly resource endeavors to provide international audiences with the highest quality research manuscripts and accounts of the constant evolution of information science and technology in whole. Researchers, academicians, practitioners and students will find this journal as a critical source of reference for all advanced technological applications and developments.

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