A Method of Incremental Data Mining Based on Genetic Programming Algorithm

A technique of genetic programming and incremental data, applied in the fields of genetic law, electrical digital data processing, special data processing applications, etc.

Active Publication Date: 2017-06-09
SHANDONG LANGCHAO YUNTOU INFORMATION TECH CO LTD
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AI Technical Summary

Problems solved by technology

[0004] Although the traditional genetic programming algorithm has no coupling between samples in the learning process, because of the encoding method and evolution mechanism, when the algorithm solves the incremental data, the learning process still needs a lot of cost regardless of the size of the incremental data.

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  • A Method of Incremental Data Mining Based on Genetic Programming Algorithm
  • A Method of Incremental Data Mining Based on Genetic Programming Algorithm
  • A Method of Incremental Data Mining Based on Genetic Programming Algorithm

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Embodiment Construction

[0054] The present invention will be described in detail below with reference to the accompanying drawings.

[0055] The purpose of the present invention is to better solve the problem of learning ability in incremental data mining. Inheriting the advantages of the genetic programming algorithm, the samples are processed one by one as the input during the learning process, and through the feedback process of multiple intermediate layers, the coefficients and offsets in the model are gradually optimized along the direction of gradient descent, so that the learning ability can be well improved.

[0056] Based on the above considerations, the concrete framework of the present invention is as follows:

[0057] (1) Determine the number of input layers; determine the function composition of the intermediate layer 1; the number of batch samples N sets the number of intermediate layers 2 in the algorithm framework; agree on the evolutionary algebra n in each input network;

[0058] (...

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Abstract

The invention provides an incremental data mining method based on a genetic programming algorithm. Incremental data mining can complete the incremental model learning task of increasing data samples from few to many, input data into the model, and the input layer performs linear mapping on the data, and the The result is transmitted to the middle layer; the middle layer performs nonlinear transformation and spatial enhancement mapping respectively, and outputs the result to the voting system; the voting system determines the category; the feedback system optimizes the network parameters. Multiple iterations complete the learning process. When processing incremental data, the coupling degree of old and new data samples is low, and old data samples are no longer considered when mining new data, which has a good inheritance.

Description

technical field [0001] The invention relates to the field of data mining, in particular to an incremental data mining model. Using the sample batch learning mode, the model combines the advantages of genetic programming and neural networks, which can well realize incremental data mining. Specifically, it is an incremental data mining method based on genetic programming algorithm. Background technique [0002] The large-scale data samples gathered in the era of big data provide possibilities for business model innovation and new scientific discoveries. How to find useful information or resources from large-scale data has become the most important problem to be solved in the era of big data. Data mining is a model discovery Technology is undoubtedly the core technology in the era of big data. [0003] In the process of data sampling, the samples collected within a certain period of time are often limited and have great limitations, and the learning model at this time often a...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30G06N3/12
CPCG06F16/2465G06N3/126G06N3/044
Inventor 杨振庚吴楠
Owner SHANDONG LANGCHAO YUNTOU INFORMATION TECH CO LTD
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