Review Article

Systematic Review on Resting-State EEG for Alzheimer’s Disease Diagnosis and Progression Assessment

Table 27

Feature selection.

Feature selection methodsArticles

AUC maximization[58, 83, 112, 122]
BFE[133]
Consistency-based filter (CBF), correlation-based feature selection (CFS), filtered subset evaluator (FSE), Chi squared (CS), gain ratio (GR), relief-, symmetrical uncertainty (SU), and ensemble feature selection (EFS)[114]
Correlation-based pursuit[129]
FCBF[140]
Fit-curve model[40]
Genetic[41, 130]
Logistic regression[107, 178]
Manual[96]
OFR[135]
value[81, 109, 126, 127, 176]
PCA[139]
Ranking by Fisher ratio score[38]
Reverse sequential feature selection[42]
SVD[77]
SVM classifier (best performers)[85, 136138]

BFE: best feature extraction; FCBF: fast correlation-based filter; OFR: orthogonal forward regression; SVD: singular value decomposition.