Multi-view data missing completion method for multi-manifold regularization non-negative matrix factorization

Abstract

The invention discloses a multi-view data missing complementing method for multi-manifold regularization non-negative matrix factorization, which comprises the following steps of: obtaining manifold and global clustering in which unmarked multi-view data tends to be consistent by utilizing a multi-manifold regularization non-negative matrix factorization algorithm through consistency assumption among multiple views; and constructing a multi-view collaborative discrimination model by adopting a view collaborative improved Gaussian mixture method. Pre-calibration of a cluster to which a sample belongs is realized by calculating the cluster relevancy level of the sample with missing data under a non-missing view angle; and establishing a missing data prediction model under a specific view angle by utilizing the consistency of multiple view angles in a low-dimensional space and adopting a multiple linear regression analysis method, thereby realizing accurate data completion under a multi-attribute missing condition. According to the method, large-scale labeled samples are not needed for training, the pre-defined category relation and related characteristics are avoided, and the understanding and discovering capacity of an existing multi-view mining technology for unlabeled multi-source data is improved.

Description

technical field [0001] The invention belongs to the technical field of machine learning for multi-view data as a research object, and specifically relates to a multi-manifold regularized non-negative matrix decomposition-based multi-view data missing complement method. Background technique [0002] With the rapid development of the Internet of Things and big data technology, the data collected by current applications has become more and more large and complex, and the multi-source and polymorphic characteristics of the data provide a basis for revealing things from different perspectives. different properties offer the possibility. For example, news event reports can be obtained from multiple news websites with different styles, different languages ​​in different countries, and various information forms such as video, audio, and pictures. In medical diagnosis, a large number of medical technologies (blood, urine, feces, and various medical instrument inspections) are used t...

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is to provide a multi-view data missing complement method based on multi-manifold regularized non-negative matrix decomposition, which can effectively avoid pre-defining category relationships and related features; In the traditional missing processing meth...

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