Data splitting system and method for validating machine learning

Abstract

A data splitting method for validating machine learning is adapted to a BP (blood pressure) dataset having a plurality of subjects and includes: dividing measurement ranges of the SBP (systolic blood pressure) data and the DBP (diastolic blood pressure) data into first intervals and second intervals; generating a plurality of classes according to the first and second intervals, wherein each class includes one of the first intervals and one of the second intervals; determining and recording a match condition of the BP data of each subject and classes, and thereby generating a plurality of match conditions corresponding the plurality of subjects, wherein each match condition includes a plurality of labels corresponding to the classes, each label has a first state or a second state; and performing a distribution procedure according to the matching conditions to distribute the BP data of subjects into a plurality of subsets.