Variable precision rough set model
Journal of Computer and System Sciences
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Approaches to knowledge reduction based on variable precision rough set model
Information Sciences—Informatics and Computer Science: An International Journal - Mining stream data
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The variable precision rough sets (VPRS) model is parametric and there are many types of knowledge reduction. Among the present various algorithms, β is introduced as prior knowledge. In some applications, it is not clear how to set the parameter. For that reason, it is necessary to seek an approach to realize the estimation of β from the decision table, avoiding the influence of β apriority upon the result. By studying relative discernibility in measurement of decision table, it puts forward algorithm of the threshold value of decision table's relative discernibility: choosing β within the interval of threshold value as a substitute for prior knowledge can get knowledge reduction sets under certain level of error classification, thus finally realizing self-determining knowledge reduction from decision table based on VPRS