EEG complexity as a biomarker for autism spectrum disorder risk

Table 3 Supervised learning classification using three different algorithms: k-nearest neighbors, support vector machine, and naïve Bayes classification^a

^aTenfold cross-validation was run using the computed mean mMSE values on 64 channels for each infant within each age group. P values were estimated empirically using a permutation of class labels approach as described in the methods section under 'classification and endophenotypes. Identical cross-validation calculations with 100 permutations were performed to determine empirical P values with three different populations: all infants, boys only and girls only. Too few 24-month-old boys were available for cross-validation. k-NN, k-nearest neighbors algorithm; SVM, support vector machine algorithm; Bayes, naïve Bayes classification algorithm. Boldface entries highlight values with statistical significance of p < 0.05.

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