Evaluating the performance of ensemble classifiers in stock returns prediction using effective features
- DOI
- 10.1016/j.eswa.2022.119186
- Published
- 2023-03
- Container
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.eswa.2022.119186,
title = {Evaluating the performance of ensemble classifiers in stock returns prediction using effective features},
author = {Masoomeh Rashidpoor Toochaei and Farzad Moeini},
year = {2023},
journal = {Expert Systems with Applications},
doi = {10.1016/j.eswa.2022.119186},
url = {https://doi.org/10.1016/j.eswa.2022.119186}
}RIS
TY - JOUR TI - Evaluating the performance of ensemble classifiers in stock returns prediction using effective features AU - Masoomeh Rashidpoor Toochaei AU - Farzad Moeini PY - 2023 JO - Expert Systems with Applications DO - 10.1016/j.eswa.2022.119186 UR - https://doi.org/10.1016/j.eswa.2022.119186 ER -
APA
Toochaei, M. R., & Moeini, F. (2023). Evaluating the performance of ensemble classifiers in stock returns prediction using effective features. Expert Systems with Applications. https://doi.org/10.1016/j.eswa.2022.119186
Source records
- crossref · retrieved 2026-11-10T13:28:02.949Z