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Multi-information fusion classification and identification method

A technology of multi-information fusion and recognition methods, applied in the field of pattern recognition and information fusion, can solve the problems of classification problems without unified and effective methods and theories

Inactive Publication Date: 2014-05-21
CHINA UNIV OF MINING & TECH (BEIJING)
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, there is no unified and effective method and theory for classification problems.

Method used

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Embodiment Construction

[0055] The present invention will be described in further detail below.

[0056] The specific content of a kind of multi-information fusion classification and identification method of the present invention is as follows:

[0057] A multi-information fusion classification and identification method is characterized in that the method is a similarity measurement method between individual objects based on multi-source information, and the steps are as follows:

[0058] (1) Let the observable characteristic parameter of the object to be classified or recognized be θ 1 ,...,θ n , normalize each of the characteristic parameters respectively, and the processed characteristic parameters are Normalization methods include:

[0059] ①If θ k The range of values ​​is [min, max],

[0060] ② If θ k The value range of is (-∞, +∞),

[0061] ③ If θ k The value range of is [min, +∞),

[0062] ④ If θ k The value range of is (-∞, max],

[0063] min and max are constants, θ k is...

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Abstract

The invention relates to the filed of mode identification and information fusion, in particular to a multi-information fusion classification and identification method. The multi-information fusion classification and identification method includes: fusing data information from different data sources, constructing a fusion classifier, and achieving classification work of classifying individual objects into a certain object class. The multi-information fusion classification and identification method achieves measurement of similarities among multiple feature objects by using similarity distance, achieves a paired choice identification method for the multiple feature objects by using internal shape diversity factors, and achieves an identification method of choosing one from multiple choices for the multiple feature objects by using combination average diversity factors.

Description

technical field [0001] The invention relates to the field of pattern recognition and information fusion, in particular to a multi-information fusion classification and recognition method. Background technique [0002] Classification is an important research area in data mining, machine learning and pattern recognition. There are many ways to solve the classification problem, and the single classification method mainly includes: [0003] (1) Decision tree [0004] Decision tree is one of the main technologies for classification and prediction. Decision tree learning is an example-based inductive learning algorithm, which focuses on inferring classification rules represented by decision trees from a set of unordered and irregular examples. . It adopts a top-down recursive method, compares the attributes at the internal nodes of the decision tree, and judges the branch downwards from the node according to different attribute values, and draws conclusions at the leaf nodes of...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/46
Inventor 孙继平洪亮
Owner CHINA UNIV OF MINING & TECH (BEIJING)
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