TABLE I.

List of frequently appearing symbols and notations in this paper.

Symbol	Description
Dj	Dataset j arranged in a n × M dimensional matrix, where j denotes a specific dataset j ∈ {1, 2, …, 11}
xi	Patient samples xi ∈ Dj, where i ∈ {1, 2, …, n}
fu(xi)	Single feature associated with xi, where u ∈ {1, 2, …, M}
F(xi)	M-dimensional gene- or protein-expression feature vector describing xi
$g_v^{\phi }(x_i)$	Transformed eigen feature obtained from F(xi), where υ denotes the index for the eigenvector, υ ∈ {1, 2, …, m}
Gφ(xi)	m-dimensional feature (embedding) vector describing xi
φ	Denotes the DR method used to create Gφ(xi), where φ ∈ {PCA, LDA, MDS, ISO, LLE, LEM}
Y(xi)	Class label for observation xi, Y ∈ {+1, −1}
${\mathcal{C}}^{\mathit{SVM}}(G^{\phi }(x_i))$	Classifier label determined via SVM applied to Gφ(xi) for all xi ∈ Dj
${\mathcal{C}}^{C4.5}(G^{\phi }(x_i))$	Classifier label determined via C4.5 decision tree applied to Gφ(xi) for all xi ∈ Dj
${\mathcal{C}}^{\mathit{ICD}}$	Inter-Centroid Distance between dominant data clusters
${\mathcal{C}}^{CT,\phi ,\mu +}$	Mean Cluster Tightness of object class +1
${\mathcal{C}}^{CT,\phi ,\mu -}$	Mean Cluster Tightness of object class −1
${\mathcal{C}}^{CT,\phi ,\sigma +}$	Standard Deviation of Cluster Tightness of object class +1
${\mathcal{C}}^{CT,\phi ,\sigma -}$	Standard Deviation of Cluster Tightness of object class −1