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Based on the theory of non-optimum analysis theory, Synthetic assessment system is studied. The system consists of three parts: single attribute analyses, multiple attribute analyses, selection analyses. Firstly, make use of the attribute set and attribute measure theory in attribute mathematics, optimum function, non-optimum function and sub-optimum function of objectives are structured, then the...
This paper proposes a novel nonlinear decision tree algorithm SSDT, spectral space decision tree. SSDT adopts spectral space transformation to extract the cluster information of data, employs decision tree to discover the decision boundary, and classifies test data with consistent mapping principle. Experimental results show that SSDT can produce higher classification accuracy and better generalization...
In allusion to the traditional case retrieval technology disadvantage of die design, a rough set-based case retrieval method is presented in the die design. To analyze and deal with die case database using rough set theory, and use a method by using grade classification and decision attributes supporting degree to discretize the quantitative features. It confirms the important degree of all types...
This paper proposes a tree classifier in the local singular vector space of data, named LST algorithm. LST builds oblique decision trees by first transforming local data on the internal nodes to the orthogonal singular vector space and then constructing univariant decision tree nodes in the new space. LST can handle datasets with totally different local and global distribution. Theoretical analysis...
The paper describes intuitionistic optimum models for attribute selection of optimum and non-optimum and deals the intuitionistic learning system of analyzing sub-optimum with the degree of knowledge understanding and credit degree of intuitionistic feature. Attribute selection of optimum and non-optimum is performed under both supervised and unsupervised learning. The task of non-optimum analysis...
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