Table 4.

Results showing p-Eigen better than AAL and PCA ROI labels. For MCI vs. Normal we report mean classification error (e.g. 0.24 ↝ 24%), whereas for Delayed Recall we report Mean Absolute Prediction Error ( ${\sum }_{i=1}^n\frac{\Vert y_i-{\widehat{y}}_i\Vert }{n}$). All the classifiers also used Base Features in addition to the graph measurement features from ROIs. The p-values from two sample t-test for p-Eigen vs AAL and PCA are 2.2 × 10⁻¹⁶.

#	FeatureSet	MCI vs. Normal (μ ± σ)	Delayed Recall (All) (μ ± σ)	Delayed Recall (Patients) (μ ± σ)
1.	AAL	0.36± 0.05	2.34 ± 0.21	1.41 ± 0.28
2.	PCA	0.34± 0.06	2.41 ± 0.35	1.35 ± 0.21
3.	p-Eigen	0.24± 0.06	1.83 ± 0.29	0.97 ± 0.18