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Parameter-adaptive density peak clustering method

A density peak, clustering method technology, applied in the direction of instruments, character and pattern recognition, calculation models, etc., can solve the problems of low clustering efficiency and large impact on calculation results, and achieve simple structure, wide application prospects, and design principles. reliable results

Inactive Publication Date: 2018-09-28
UNIV OF JINAN
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  • Application Information

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Problems solved by technology

[0004] Existing clustering algorithms need to set initial parameters to achieve clustering, and the initial parameters have a great influence on the calculation results, requiring accurate prior knowledge to set parameter values, resulting in the defect of low clustering efficiency

Method used

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  • Parameter-adaptive density peak clustering method
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  • Parameter-adaptive density peak clustering method

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Embodiment Construction

[0042] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. The following embodiments are explanations of the present invention, but the present invention is not limited to the following embodiments.

[0043] like Figure 1-7 As shown, a parameter-adaptive density peak clustering method provided in this embodiment includes the following steps:

[0044] First, model and analyze the data set, and use the curve fitting method to automatically obtain the threshold value of the distance δ between the local density ρ and the higher density neighbor points in the data, and calculate all The value of its ρ and δ for the data point.

[0045] For the cluster head point, the values ​​of ρ and δ are both large, define the variable γ=ρ*δ, and establish a function curve such as formula (6):

[0046]

[0047] where a i is the coefficient of the curve function, I c It is a collection of serial numbers of data poin...

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Abstract

The invention relates to a parameter-adaptive density peak clustering method. The method is characterized by comprising the following steps of: S1, automatically obtaining a data role on the basis ofa data density attribute; S2, realizing automatic clustering by taking a cluster head node as a core; and S3, evaluating a clustering result, adaptively adjusting clustering parameters and iterative optimizing the clustering result.

Description

technical field [0001] The invention belongs to the technical field of network data communication, and relates to a clustering method used in the communication field, in particular to a parameter adaptive density peak clustering method. Background technique [0002] With the rapid development of hardware technology, network communication technology, various sensing devices and various information technologies, in social networks, sensor networks, e-commerce, network monitoring, meteorological environment monitoring, financial retail enterprises and other application fields, there are A large amount of dynamic data, how to obtain effective knowledge from these data has become a hot spot in big data application research. [0003] Cluster analysis is an unsupervised machine learning method, which can effectively divide data without setting sample data sets for training, so it has a good application prospect in the field of big data analysis. At present, clustering algorithm ha...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06N99/00
CPCG06F18/23
Inventor 杜韬许婧文曲守宁王玉栋武奎庞战牟国栋李国昌张瑞刘闯
Owner UNIV OF JINAN