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. Author manuscript; available in PMC: 2015 May 19.
Published in final edited form as: Conf Proc IEEE Eng Med Biol Soc. 2009;2009:2719–2722. doi: 10.1109/IEMBS.2009.5333386

Fig. 5.

Fig. 5

(a) Classifier output (h(x) − b, Eq. (3)) values for the two classes. The thick line is the classification boundary and the dotted lines are the margins. Values above the thick line indicate autism and those below indicate control subjects. Examples inside the margins are harder examples. (b) ROC curve shows that our classifier can perform reasonably well with an area under curve (AUC) of 0.7645. Average specificity and sensitivity is 71.88%. The values are estimated using leave-one-out cross validation.