Data clustering method and system, and data processing equipment

Abstract

The invention is applicable to the field of data processing, provides a data clustering method, a data clustering system and data processing equipment. The method comprises the following steps: inputting a data set consisting of n objects with a block data feature required to be clustered and an expected class number k; selecting k block data objects from the data set to serve as an initial class center; calculating the distance from each object to the initial class center; distributing each block data object to the center closest to the block data object according to the calculated distance to form k disjointed classes; calculating the center of each class to serve as a new class center; repeatedly executing the step of distributing each block data object to the center closest to the block data object according to the calculated distance to form the k disjointed classes and the step of calculating the center of each class to serve as the new class center until the algorithm is converged; obtaining the division result of the data set. By the data clustering method, the data clustering system, and the data processing equipment, the data with the block feature can be processed directly without compressing the block data, so that the loss of information is avoided, and the obtained clustering result is better than the clustering effect obtained after the block data is compressed.

Description

technical field [0001] The invention belongs to the field of data processing, and in particular relates to a data clustering method, system and data processing equipment. Background technique [0002] With the rapid development of data automatic generation and collection technology, many fields have produced massive data that record the details of people's behavior, which provides the possibility for behavior pattern mining. These data describing the behavior of the collected objects have a common feature, that is, the behavior of each object is described by a collection of multiple records. We call the data set that records the behavior characteristics of the object a block of data. For example, a customer's purchase behavior or call behavior is reflected by the customer's purchase details or call details in a certain period of time. Through in-depth mining of block data, it helps us analyze and predict customer behavior. However, current machine learning algorithms canno...

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Problems solved by technology

[0003] The purpose of the present invention is to provide a data clustering method, system and data processing equipment, aiming to solve the problem that the current machine learning algorithm in the prior art cannot directly process the block data, and it must be converted into standard data for processing. Dealing with issues where underlying behavioral features present in the data may be overlooked

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