Clustering cluster calculation method and device, terminal and storage medium

A computing method and clustering technology, applied in the field of information processing, can solve the problem of low accuracy of the number of clusters, and achieve the effect of accurate acquisition

Inactive Publication Date: 2020-02-21
SHENZHEN UNIV
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Problems solved by technology

[0003] In view of this, the present invention provides a cluster calculation method, device, terminal and storage medium, which are used to solve the problem in the prior art that the accuracy of the number of clusters obtained based on user experience is low

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  • Clustering cluster calculation method and device, terminal and storage medium
  • Clustering cluster calculation method and device, terminal and storage medium
  • Clustering cluster calculation method and device, terminal and storage medium

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Embodiment Construction

[0054] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0055] In order to solve the problem that in traditional technology, data clustering needs to be obtained in combination with user experience and background knowledge in related fields, and the accurate acquisition of the number of clusters cannot be achieved. In this embodiment, a cluster calculation method is proposed, and the implementation of the method may depend on a computer program that can run on a computer system based on the Von Neumann architecture.

[...

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Abstract

The embodiment of the invention discloses a clustering cluster calculation method and device, a terminal and a storage medium. The method comprises the following steps: acquiring target feature data of communication equipment contained in a sample equipment set at a preset time magnitude within a preset duration, and constructing a standard initial matrix according to the target feature data; extracting a preset number of communication equipment samples from the sample equipment set, and constructing a clustering center matrix according to the target feature data corresponding to the preset number of communication equipment samples; calculating a target distance value between each row of elements in the clustering center matrix and all rows of elements in the standard initial matrix, and constructing a distance vector; and calculating the number of class clusters contained in the target feature data by adopting a parameter-window-free function probability density estimation method based on the distance vector. In addition, the embodiment of the invention further discloses a multi-dimensional time series clustering cluster calculation device, a terminal and a computer readable medium. According to the invention, the method can achieve the precise obtaining of the number of multi-dimensional class clusters.

Description

technical field [0001] The present invention relates to the technical field of information processing, in particular to a cluster computing method, device, terminal and storage medium. Background technique [0002] Cluster analysis refers to the analytical process of grouping a collection of physical or abstract objects into multiple classes consisting of similar objects. Among them, a core problem in cluster analysis is that the number of clusters in the data must be known in advance, because many clustering algorithms need to input the number of clusters (number of clusters) as a parameter to run the algorithm. However, the number of clusters present in real data is usually unknown. In practical applications, the existing methods for determining the optimal number of clusters are mainly researched on numerical attribute data, and the data distribution structure is usually convex blob data. Specifically combining the clustering algorithm and the internal validity index, a...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/28
CPCG06F16/285
Inventor 魏丞昊
Owner SHENZHEN UNIV
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