A Multi-view Decision Model Based on CCA
Three-way decision theory divides all samples into three regions: positive region, negative region and boundary region. A lack of detailed information may make a definite decision impossible for samples in boundary region. These samples may be further handled by using new information. In this paper, we propose a method Multi-View Decision Model based on constructive three-way decision theory. Multi-view Decision Model mines the global information of all samples for decision. All samples firstly are decided by MinCA, which builds the min covers for each class. Then samples in boundary region are classified using Multi-view information. Experiments have shown that in most cases, Multi-View Decision Model is beneficial for reducing boundary region and promoting classification precision.
KeywordsBoundary region Multi-view information Three-way decision theory MinCA
This work is supported by the National Natural Science Foundation of China (No. 61175046, No. 61402006), supported by Provincial Natural Science Research Program of Higher Education Institutions of Anhui Province (No. KJ2013A016), and supported by Open Funding Project of Co-Innovation Center for Information Supply & Assurance Technology of Anhui University (No. ADXXBZ201410).
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