A comprehensive evaluation of ensemble learning for stock-market prediction

A comprehensive evaluation of ensemble learning for stock-market prediction

Abstract Stock-market prediction using machine-learning technique aims at developing effective and efficient models that can provide a better and higher rate of prediction accuracy. Numerous ensemble regressors and classifiers have been applied in stock market predictions, using different combinatio...

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Bibliographic Details
Main Authors: Isaac Kofi Nti, Adebayo Felix Adekoya, Benjamin Asubam Weyori
Format: Article
Language:English
Published: SpringerOpen 2020-03-01
Series:Journal of Big Data
Subjects:
Machine-learning
Ensemble-classifiers
Artificial intelligence
Predictions
Ensemble-regressors
Stacking
Online Access:http://link.springer.com/article/10.1186/s40537-020-00299-5

Internet

http://link.springer.com/article/10.1186/s40537-020-00299-5

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