A New SSOPMV Learning for Matrix Data Sets

[摘要] In real-world applications, most multi-view data sets are semi-supervised and large-scale. In order to process these data sets, scholars have developed semi-supervise done-pass multi-view learning (SSOPMV). While SSOPMV cannot process matrix data sets. Thus this manuscript extends the model of SSOPMV to matrix version and the new learning machine is named matrix-instance-based SSOPMV, i.e. (MSSOPMV). Related experiments validate that MSSOPMV can process multi-view, semi-supervised, large-scale, and matrix data sets well.

[发布机构] College of Information Engineering, Shanghai Maritime University, No. 1550, LinGang Ave., Shanghai, China^1

[效力级别] 无线电电子学 [学科分类] 计算机科学（综合）

[关键词] Learning machines;Multi-view datum;Multi-view learning;Multi-views;Process matrix;Real-world;Semi-supervised