HDEC: A Heterogeneous Dynamic Ensemble Classifier for Binary Datasets
In recent years, ensemble classification methods have been widely investigated in both industry and literature in the field of machine learning and artificial intelligence. The main advantage of this approach is to benefit from a set of classifiers instead of using a single classifier with the aim o...
Main Authors: | Nasrin Ostvar, Amir Masoud Eftekhari Moghadam |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2020-01-01
|
Series: | Computational Intelligence and Neuroscience |
Online Access: | http://dx.doi.org/10.1155/2020/8826914 |
Similar Items
-
A New Revision of the HDEC (Henry Draper Extension Charts) Catalog
by: Ashimbaeva N., et al.
Published: (2016-03-01) -
A COMPARATIVE STUDY ON PERFORMANCE OF BASIC AND ENSEMBLE CLASSIFIERS WITH VARIOUS DATASETS
by: Gunakala, A., et al.
Published: (2023) -
Multi-objective and semi-supervised heterogeneous classifier ensembles
by: Gu, Shenkai
Published: (2017) -
Imbalanced Ensemble Classifier for Learning from Imbalanced Business School Dataset
by: Tanujit Chakraborty
Published: (2019-08-01) -
An Adaptive Heterogeneous Online Learning Ensemble Classifier for Nonstationary Environments
by: Tinofirei Museba, et al.
Published: (2021-01-01)