Machine-learning program reveals genes responsible for sex-specificdifferences in Alzheimer'sdisease progression NatureComms
). In MultiLayerPerceptron classifier, we used backpropagation with learning rate of 0.3, momentum of 0.2 and 4 hidden layers. In PART classifier, the confidence threshold for pruning is set to 0.25 and the minimum 5 objects per leaf is used. In Random Forest classifier we used 10 trees. In JRip classifier we used 3 folds, where one fold is used as pruning set, minimal weights of instances within a split is set to 2, with 2 runs of optimization.
In order to build these predictive models, input data must first be reformatted. For predictive models based on EAML genes, this reformatting was done as follows. Consider any one sample
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