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A mobile phone feature detection optimization improvement algorithm based on a C4.5 decision tree

A technology for feature detection and algorithm improvement, applied in computing, computer parts, instruments, etc., to achieve the effect of increasing credibility

Inactive Publication Date: 2019-06-14
ELECTRIC POWER RES INST OF STATE GRID ZHEJIANG ELECTRIC POWER COMAPNY +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In recent years, the theft of mobile phones has become one of the important reasons for threatening the security of mobile phones. However, there are few methods or tools that can protect mobile phones from being used by strangers.

Method used

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  • A mobile phone feature detection optimization improvement algorithm based on a C4.5 decision tree
  • A mobile phone feature detection optimization improvement algorithm based on a C4.5 decision tree
  • A mobile phone feature detection optimization improvement algorithm based on a C4.5 decision tree

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Embodiment Construction

[0024] The present invention will be further described below in conjunction with the examples, but the protection scope of the present invention is not limited to the following examples. Within the spirit of the present invention and the protection scope of the claims, any modification and change made to the present invention will fall into the protection scope of the present invention.

[0025] This embodiment provides a mobile phone feature detection optimization algorithm based on the C4.5 decision tree. On the basis of the existing C4.5 algorithm, in the process of calculating the information gain and information gain ratio of each factor, the division of different factors is given A weight parameter β, defined as follows:

[0026] For each different factor A, suppose n different subsets obtained after dividing according to factor A correspond to n different results A'={A 1 ,A 2 ,...,A n}, so assuming that the weight parameter for different results of factor A is A β =...

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Abstract

The invention discloses a mobile phone feature detection optimization improvement algorithm based on a C4.5 decision tree. The method is based on a C4.5 algorithm, and in the process of calculating the information gain and the information gain ratio for each factor, a weight parameter is given aiming at the division of different factors, so that the information gain degree data difference of different factors is greater than that of the prior art, the recognition of machine learning on the use characteristic difference of different users is improved, and the credibility of a result is improved. According to the method and the device, the use characteristics of the mobile phone user are analyzed and recorded, and the characteristics of the current mobile phone user are matched with the characteristics of the mobile phone user, so that whether the mobile phone user is legal or not is judged, and the mobile phone cannot be illegally used by a third-party user. The invention aims to improve the mobile phone feature detection accuracy by improving and optimizing a C4.5 decision tree machine learning algorithm and more accurately identify illegal use operations of the mobile phone.

Description

technical field [0001] The invention belongs to the field of electronic machine learning algorithms, in particular to a mobile phone feature detection optimization improvement algorithm based on C4.5 decision tree. Background technique [0002] In recent years, with the popularization of mobile phones and the diversification of mobile phone applications, mobile phones have played an increasingly important role in human life. However, with the rapid development of mobile phones, the threats faced by mobile phones are also increasing. The widespread use of 4G networks, the increasingly powerful functions of mobile phones, and the increasingly close connection between mobile phones and daily life are all important reasons for the increasing number of threats. As of this year, my country's mobile phone users have reached 1.256 billion, covering most of the population. At the same time, according to "Smartphone Users' Perception and Response to Mobile Security Threats" publishe...

Claims

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Application Information

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IPC IPC(8): G06F21/55G06K9/62
Inventor 孙歆汪自翔李沁园孙昌华
Owner ELECTRIC POWER RES INST OF STATE GRID ZHEJIANG ELECTRIC POWER COMAPNY
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