Research on stock trend prediction method based on optimized random forest
Abstract As a complex hot problem in the financial field, stock trend forecasting uses a large amount of data and many related indicators; hence it is difficult to obtain sustainable and effective results only by relying on empirical analysis. Researchers in the field of machine learning have proved...
Main Authors: | Lili Yin, Benling Li, Peng Li, Rubo Zhang |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2023-03-01
|
Series: | CAAI Transactions on Intelligence Technology |
Subjects: | |
Online Access: | https://doi.org/10.1049/cit2.12067 |
Similar Items
-
Perbandingan Kinerja Algoritma Optimasi pada Metode Random Forest untuk Deteksi Kegagalan Jantung
by: Unang Sunarya, et al.
Published: (2022-12-01) -
eGAP: An Evolutionary Game Theoretic Approach to Random Forest Pruning
by: Khaled Fawagreh, et al.
Published: (2020-11-01) -
Optimal Feature Set Size in Random Forest Regression
by: Sunwoo Han, et al.
Published: (2021-04-01) -
Review of Random Survival Forest method
by: Majid Rezaei, et al.
Published: (2020-10-01) -
On the Optimal Size of Candidate Feature Set in Random forest
by: Sunwoo Han, et al.
Published: (2019-03-01)