Table 2.

Notations

Symbol	Definition and Description
D =  < X, y>	Labeled dataset where X ∈ Rm × n is a matrix of m instances and n features, and y ∈ {0, 1}m is the binary class labels of the instances
xi	ith feature in X
g(xi, xj)	Function that returns the redundancy between two features xi and xj
f(xi, y)	Function that returns the relevance between a feature xi and class labels y
S	Indices of selected features
Ω	Indices of all features
ΩS	Indices of candidate features Ω − S
k	Number of features to be selected
v	Number of views in a multi-view dataset
MVD =  < (X1, …, Xv), y>	Labeled multi-view dataset where $X^i\in R^{m\times n_i}$ is a matrix of m samples and ni features and y ∈ {0, 1}m is the binary class labels of the instances in all views
Di =  < Xi, y>	ith view in a multi-view dataset
${\mathrm{x}}_{\mathrm{j}}^{\mathrm{i}}$	jth feature in Xi
Si	Indices of selected features from ith view
Ωi	Indices of all features in ith view
${\mathrm{\Omega }}_{S^i}$	Indices of candidate features Ωi − Si in ith view