BIG DATA PROCESSING METHOD FOR SEGMENT-BASED TWO-GRADE DEEP LEARNING MODEL
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Mar 31, 2015
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Mar 13, 2015
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Abstract
A big data processing method for a segment-based two-grade deep learning model. The method includes: step (1), constructing and training a segment-based two-grade deep learning model, wherein the model is divided into two grades in a longitudinal level: a first grade and a second grade, each layer of the first grade is divided into M segments in a horizontal direction, and the weight between neuron nodes of adjacent layers in different segments of the first grade is zero; step (2), dividing big data to be processed into M sub-sets according to the type of the data and respectively inputting same into M segments of a first layer of the segment-based two-grade deep learning model for processing; and step (3), outputting a big data processing result. The method of the present invention can increase the big data processing speed and shorten the processing time.
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