Model selection for medical diagnosis decision support systems
Decision Support Systems
Multisurface Proximal Support Vector Machine Classification via Generalized Eigenvalues
IEEE Transactions on Pattern Analysis and Machine Intelligence
Test Strategies for Cost-Sensitive Decision Trees
IEEE Transactions on Knowledge and Data Engineering
Twin Support Vector Machines for Pattern Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Data preparation for sample-based face detection
International Journal of Computer Applications in Technology
Construct support vector machine ensemble to detect traffic incident
Expert Systems with Applications: An International Journal
International Journal of Computer Applications in Technology
Pattern Recognition and Neural Networks
Pattern Recognition and Neural Networks
SMOTE: synthetic minority over-sampling technique
Journal of Artificial Intelligence Research
Support vector machine based multiagent ensemble learning for credit risk evaluation
Expert Systems with Applications: An International Journal
On selection and combination of weak learners in AdaBoost
Pattern Recognition Letters
A new approach for texture classification in CBIR
International Journal of Computer Applications in Technology
Pattern Classification Using Ensemble Methods
Pattern Classification Using Ensemble Methods
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
An intelligent tool for syntactic annotation of Arabic corpora
International Journal of Computer Applications in Technology
Optimising of support plans for new graduate employment market using reinforcement learning
International Journal of Computer Applications in Technology
Using support vector machine for characteristics prediction of hydraulic valve
International Journal of Computer Applications in Technology
Computational Biology and Chemistry
Probabilistic outputs for twin support vector machines
Knowledge-Based Systems
Improvements on Twin Support Vector Machines
IEEE Transactions on Neural Networks
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In this paper, to improve the generalisation ability of generalised eigenvalues proximal support vector machines GEPSVM, we propose an ensemble GEPSVM, called EnGEP for short. Note that GEPSVM is not sensitive to different weights of the points, to increase the potential diversity of GEPSVM, firstly, we introduce an extra parameter in GEPSVM, which gives different penalties for two non-hyperplanes determines by GEPSVM. Then, we use a novel bagging strategy to ensemble GEPSVM with additional parameters. Experimental results both on artificial and benchmark datasets show that our EnGEP improves the generalisation performance of GEPSVM greatly, and it also reveals the effectiveness of our EnGEP.