Rough Set Based Decision Support

摘要: In this chapter, we are concerned with discovering knowledge from data. The aim is to find concise classification patterns that agree situations described by the Such useful for explanation of data and prediction future situations. They particularly in such decision problems as technical diagnostics, performance evaluation risk assessment. a set attributes, which might also call properties, features, characteristics, etc. attributes may be either input or output situation. These refer states, examples, Within will them objects. goal chapter present discovery paradigm multi-attribute multicriteria making, based upon concept rough sets. Rough theory was introduced (Pawlak 1982, Pawlak 1991). Since then, it has often proved an excellent mathematical tool analysis vague description adjective (referring quality information) inconsistency ambiguity. philosophy on assumption every object universe U there associated certain amount information (data, knowledge). This can expressed means number attributes. describe object. Objects have same said indiscernible (similar) respect available information.