Comparison of rough-set and statistical methods in inductive learning
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2016, Expert Systems with ApplicationsCitation Excerpt :There are numerous studies comparing the RS approach with other methods. Already Wong, Ziarko, and Ye (1986) have compared the RS approach with statistical methods in machine learning, showing that the RS-based concept of approximate classification is closely related to the statistical approach. Zhong, Dong, and Ohsuga (2001) discusses some disadvantages of two feature selection methods for selecting relevant attributes, namely the filter approach and the wrapper approach, comparing them to the RS approach.
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2016, International Journal of Production EconomicsCitation Excerpt :However, these two approaches are apparently very different. In both methods, objects in the knowledge base are assumed to be characterized by “attributes and attribute values” (Wong et al., 1986). In the decision tree, the rule generated from the complete attribute tree.
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2014, International Journal of Approximate ReasoningCitation Excerpt :Example 1 continued In the earlier studies, Wong et al. used the confidence and resolution factor for inductive learning [42]. Tsumoto proposed the accuracy and coverage to measure the degree of sufficiency and necessity, respectively, and acquired classification rules with high accuracy and high coverage [40].