Table 5. Summary of classifier performance.

Model	Testing Dataset	Sensitivity[95% CI]	Specificity[95% CI]	Best CVA[95% CI]	Noise/Not Noise
M1	SchizophreniaSame institution, same scanner	0.890.86 0.93	0.830.78 0.87	0.860.83 0.88	343 (295)
M1	NKI Rockland InstituteDifferent institution, same scanner	0.880.86 0.90	0.880.86 0.91	0.880.86 0.89	947 (711)
M1	Human Connectome DatabaseDifferent institution, different scanner	0.720.68 0.77	0.920.88 0.95	0.790.75 0.82	451 (230)

Performance metrics (sensitivity, specificity, and best cross validation accuracy (CVA)) and proportion of noise components in data for model of all comprehensive noise (All Noise, M1) built with Data A and tested with ten -fold cross validation on three novel datasets: Data B (same institution, same scanner, different subject population), Data C (different institution, same scanner), Data D (different institution, different scanner).