Fig 1. Feature-to-classifier mapping.

Video analysts scored each video with 30 features. This matrix shows which feature corresponds to which classifier. Darker colored features indicate higher overlap, and lighter colors indicate lower overlap across the models. The features are rank ordered according to their frequency of use across the 8 classifiers. Further details about the classifiers are provided in Table 1. The bottom 7 features were not part of the machine learning process but were chosen because of their potential relationship with the autism phenotype and for use in further evaluation of the models’ feature sets when constructing a video feature–specific classifier. ADTree7, 7-feature alternating decision tree; ADTree8, 8-feature alternating decision tree; LR5, 5-feature logistic regression classifier; LR10, 10-feature logistic regression classifier; SVM5, 5-feature support vector machine; SVM10, 10-feature support vector machine; SVM12, 12-feature support vector machine.