HDEC: A Heterogeneous Dynamic Ensemble Classifier for Binary Datasets
Joint Authors
Ostvar, Nasrin
Eftekhari Moghadam, Amir Masoud
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-14
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
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 of improving the prediction performance, such as accuracy.
Selecting the base classifiers and the method for combining them are the most challenging issues in the ensemble classifiers.
In this paper, we propose a heterogeneous dynamic ensemble classifier (HDEC) which uses multiple classification algorithms.
The main advantage of using heterogeneous algorithms is increasing the diversity among the base classifiers as it is a key point for an ensemble system to be successful.
In this method, we first train many classifiers with the original data.
Then, they are separated based on their strength in recognizing either positive or negative instances.
For doing this, we consider the true positive rate and true negative rate, respectively.
In the next step, the classifiers are categorized into two groups according to their efficiency in the mentioned measures.
Finally, the outputs of the two groups are compared with each other to generate the final prediction.
For evaluating the proposed approach, it has been applied to 12 datasets from the UCI and LIBSVM repositories and calculated two popular prediction performance metrics, including accuracy and geometric mean.
The experimental results show the superiority of the proposed approach in comparison to other state-of-the-art methods.
American Psychological Association (APA)
Ostvar, Nasrin& Eftekhari Moghadam, Amir Masoud. 2020. HDEC: A Heterogeneous Dynamic Ensemble Classifier for Binary Datasets. Computational Intelligence and Neuroscience،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1138868
Modern Language Association (MLA)
Ostvar, Nasrin& Eftekhari Moghadam, Amir Masoud. HDEC: A Heterogeneous Dynamic Ensemble Classifier for Binary Datasets. Computational Intelligence and Neuroscience No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1138868
American Medical Association (AMA)
Ostvar, Nasrin& Eftekhari Moghadam, Amir Masoud. HDEC: A Heterogeneous Dynamic Ensemble Classifier for Binary Datasets. Computational Intelligence and Neuroscience. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1138868
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1138868