Artificial intelligence training method for a target model based on the label matrix

A data processing system, comprising:

• a sensor configured for sensing target information of a target device;
• a receiver communicatively connected to the sensor and configured for receiving and processing the target information to form feature information;
• a label processor communicatively connected to the receiver and configured for processing the feature information into a label matrix, wherein a target model is established by an artificial intelligence training method based on the label matrix, and wherein the label processor processes the feature information by using a cumulative method and a principal component analysis method, the cumulative method converts the feature information before accumulation into a cumulative feature after accumulation, and the label processor obtains the label matrix by calculating the cumulative feature after accumulation according to the principal component analysis method and a min-max normalization method;
• and
• a predictor communicatively connected to the receiver and the label processor and configured for predicting a life limit of the target device via the target model after real-time information of the target device is captured, wherein a content of the target information is corresponding to a content of the real-time information.