Sparsity-driven weighted ensemble classifier
In this study, a novel sparsity-driven weighted ensemble classifier (SDWEC) that improves classification accuracy and minimizes the number of classifiers is proposed. Using pre-trained classifiers, an ensemble in which base classifiers votes according to assigned weights is formed. These assigned we...
Main Authors: | Atilla Özgandür, Fatih Nar, Hamit Erdem |
---|---|
Format: | Article |
Language: | English |
Published: |
Atlantis Press
2018-01-01
|
Series: | International Journal of Computational Intelligence Systems |
Subjects: | |
Online Access: | https://www.atlantis-press.com/article/25894608/view |
Similar Items
-
Ensemble Classifier Modelling for Dealing with Missing Values
by: Hasan, Mohammad Rajib
Published: (2020) -
Automatic Recommendation Method for Classifier Ensemble Structure Using Meta-Learning
by: Robercy Alves Da Silva, et al.
Published: (2021-01-01) -
Metagenomic Geolocation Prediction Using an Adaptive Ensemble Classifier
by: Samuel Anyaso-Samuel, et al.
Published: (2021-04-01) -
Dual-Layer Deep Ensemble Techniques for Classifying Heart Disease
by: Jothi Prakash, V., et al.
Published: (2022) -
Prediction of plant lncRNA by ensemble machine learning classifiers
by: Caitlin M. A. Simopoulos, et al.
Published: (2018-05-01)