Stock Market Prediction Performance Analysis by Using Machine Learning Regressor Techniques

Author:

Padhy Neelamadhab,Dharmireddi Srinivasarao,Padhy Dushmanta Kumar,Saikrishna R.,Raju K. Srujan

Publisher

Springer Nature Switzerland

Reference15 articles.

1. Padhi, D.K., Padhy, N., Bhoi, A.K., Shafi, J., Ijaz, M.F.: A fusion framework for forecasting financial market direction using enhanced ensemble models and technical indicators. Mathematics 9(21), 2646 (2021)

2. Dhupia, B.: Ensemble machine learning modelling for medium to long term energy consumption forecasting. Turk. J. Comput. Math. Educ. (TURCOMAT) 12, 459–463 (2021)

3. Kadiyala, A., Kumar, A.: Applications of python to evaluate the performance of bagging methods. Environmental Progress & Sustainable Energy, Wiley Online Library (2018)

4. Kadiyala, A., Kumar, A.: Applications of Python to evaluate the performance of decision tree-based boosting algorithms. Environ. Prog. Sustain. Energy 37, 618–623 (2017)

5. Krollner, B., Vanstone, B., Finnie, G.: Financial time series forecasting with machine learning techniques: a survey. In: Proceedings of the 18th European Symposium on Artificial Neural Networks (ESANN 2010) (2010)

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