Table 3.

Results showing p-Eigen better than just using the Base Features. For MCI vs. Normal we report mean classification error (e.g. 0.24 ↝ 24%), whereas for Delayed Recall we report Mean Absolute Prediction Error ( ${\sum }_{i=1}^n\frac{\Vert y_i-{\widehat{y}}_i\Vert }{n}$). The p-values from two sample t-tests for all columns are 2.2 × 10⁻¹⁶.

Feature Set	MCI vs. Normal (μ ± σ)	Delayed Recall (All) (μ ± σ)	Delayed Recall (Patients) (μ ± σ)
Base Features	0.42 ± 0.08	2.68 ± 0.35	1.47 ± 0.30
+ p-Eigen	0.24 ± 0.06	1.83 ± 0.29	0.97 ± 0.18