Application of Normalized Decision Measures to the New Case Classification

The optimization of rough set based classification models with respect to parameterized balance between a model's complexity and confidence is discussed. For this purpose, the notion of a parameterized approximate inconsistent decision reduct is used. Experimental extraction of considered models from real life data is described.

• Type: Conference
• Year: 2000
• Where: RSCTC
• Authors: Dominik Slezak, Jakub Wroblewski
• Keywords: Fuzzy Logic, Inconsistent Decision Reduct, Parameterized Balance, RSCTC 2000, Set Based Classification