1. A data processing method comprising: setting a learning data set including a plurality of learning data having respective labels to an uppermost node of a decision tree; setting selection probabilities of the learning data; selecting a combination of the learning data from each of a plurality of sets of learning data assigned to nodes of the decision tree in accordance with the selection probabilities; determining a branch rule for dividing one of the sets of the learning data assigned to the nodes of the decision tree into at least two subsets using the selected combination of the learning data; and assigning the subsets divided in accordance with the branch rule to nodes in a lower level.