Sample acquisition method, device and equipment for hard disk data fault prediction

The invention relates to the field of machine learning, in particular to a sample obtaining method, device and equipment for hard disk data fault prediction, and the method comprises the steps: obtaining a training sample of hard disk data and a sample label corresponding to the training sample; constructing a first fault model for generating a virtual sample according to the training sample; constructing a second fault model of a virtual label corresponding to the generated virtual sample according to the sample label; determining the virtual sample and the virtual label according to a training sample, a sample label, a first fault model and a second fault model; and obtaining a target training sample for hard disk data fault prediction and a target sample label corresponding to the target training sample according to the virtual sample and the virtual label. According to the method, a mode of combining machine learning and mixed learning is utilized, a common data imbalance problem in the hard disk fault fi