A comprehensive survey on ECG signals as new biometric modality for human authentication: Recent advances and future challenges
AN Uwaechia, DA Ramli - IEEE Access, 2021 - ieeexplore.ieee.org
Electrocardiogram (ECG) has extremely discriminative characteristics in the biometric field
and has recently received significant interest as a promising biometric trait. However, ECG …
and has recently received significant interest as a promising biometric trait. However, ECG …
A machine learning approach combining expert knowledge with genetic algorithms in feature selection for credit risk assessment
PZ Lappas, AN Yannacopoulos - Applied Soft Computing, 2021 - Elsevier
Most credit scoring algorithms are designed with the assumption to be executed in an
environment characterized by an automatic processing of credit applications, without …
environment characterized by an automatic processing of credit applications, without …
Building an open source classifier for the neonatal EEG background: a systematic feature-based approach from expert scoring to clinical visualization
S Montazeri, E Pinchefsky, I Tse, V Marchi… - Frontiers in human …, 2021 - frontiersin.org
Neonatal brain monitoring in the neonatal intensive care units (NICU) requires a continuous
review of the spontaneous cortical activity, ie, the electroencephalograph (EEG) background …
review of the spontaneous cortical activity, ie, the electroencephalograph (EEG) background …
[HTML][HTML] A lexicographic cooperative co-evolutionary approach for feature selection
This paper starts with two hypotheses. The first one is that the simultaneous optimization of
the hyperparameters regulating the classifier within a wrapper method, while the best subset …
the hyperparameters regulating the classifier within a wrapper method, while the best subset …
A Novel Feature Selection with Many-Objective Optimization and Learning Mechanism
L Shu, F He, X Hu, H Li - 2021 IEEE 24th International …, 2021 - ieeexplore.ieee.org
Feature selection is extremely important in machine learning and data mining. Typical two-
objective feature selection methods aim to minimize the number of features and maximize …
objective feature selection methods aim to minimize the number of features and maximize …
An entropy driven multiobjective particle swarm optimization algorithm for feature selection
J Luo, D Zhou, L Jiang, H Ma - 2021 IEEE Congress on …, 2021 - ieeexplore.ieee.org
Feature selection is an important research field in machine learning since high-
dimensionality is a common characteristic of real-world data. It has two main objectives …
dimensionality is a common characteristic of real-world data. It has two main objectives …
A lexicographic cooperative co-evolutionary approach for feature selection
J González Peñalver, J Ortega Lopera… - 2021 - digibug.ugr.es
This paper starts with two hypotheses. The first one is that the simultaneous optimization of
the hyperparameters regulating the classifier within a wrapper method, while the best subset …
the hyperparameters regulating the classifier within a wrapper method, while the best subset …