Adaptive multi-view clustering method based on paired synergetic regularization and NMF

Abstract

The invention proposes an adaptive multi-view clustering method based on paired synergetic regulation and NMF, and the method is designed to resolve the technical problem of a currently available multi-view clustering method that the precision is low and the normalized interactive information is also low. The method comprises the following steps: obtaining the normalized non-negative multi-view data of an original image set; calculating the Laplacian matrix for the multi-view data; constructing an objective function for adaptive multi-view clustering based on paired synergetic regularization and NMF; obtaining the iteratively updated expressions for the base matrix, the coefficient matrix and the weight parameters respectively; obtaining the updated base matrix, the coefficient matrix and weight parameters; and performing K-means clustering on the updated coefficient matrix to obtain the clustering result. According to the invention, through the use of a paired synergetic regulation method to keep the similarities of the views and through the use of the adaptive method to automatically learn the weight parameters for the similarity constraining items in the views, the multi-view clustering function is increased effectively so that the function can be applied for fields in user information analyzing, financial analyzing, medical science.

Description

technical field [0001] The invention belongs to the technical field of computer vision and pattern recognition, and relates to an adaptive multi-view clustering method, in particular to an adaptive multi-view clustering method based on pairwise collaborative regularization and NMF, which can be applied to customer information analysis, areas such as financial analysis and medicine. Background technique [0002] With the rapid development of technologies such as the Internet, information collection and information retrieval, the amount of data has increased dramatically, and the information society has entered the era of big data. Therefore, how to extract information that can be used by us from massive data has become an urgent task of modern science. As a result, data mining came into being and became a kind of data information processing technology. Clustering is an important analysis tool and method for data processing in the field of data mining, and it is also an impo...

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Problems solved by technology

[0007] The purpose of the present invention is to address the deficiencies in the prior art above, and propose an adaptive multi-view clustering method based on pairwise cooperative regularization and NMF, which is used to solve the low precision existing in the existing multi-view clustering methods and the technical problem of low normalized mutual information

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