Ensembles of Multiobjective-Based Classifiers for Detection of Epileptic Seizures
Multi-objective Optimization
Ensemble Learning
Medical Diagnosis
Fernando S Beserra, Marcos M Raimundo, Fernando J Von Zuben (2017). Iberoamerican Congress on Pattern Recognition.
Abstract
This paper proposes multiobjective-based classifiers to detect epileptic seizures using ensemble approaches, transfer-learning methods, and three alternative feature extraction techniques. Two aspects of the problem were investigated: (1) the relative merit of distinct proposals to synthesize an ensemble of classifiers, considering all the three feature extraction techniques; (2) the potential of an ensemble composed of transfer-learned classifiers. The blend approaches with the best performance detected all test seizures, with a high proportion of correctly detected samples inside the seizure interval and high proportion of time intervals correctly classified as non-seizures.
