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Variable Precision Rough Sets
Variable precision rough sets
Introduction

A rough set theory (RST) innovation has been the development by Ziarko (1993) of a variable precision rough sets (VPRS) model, which incorporates probabilistic decision rules. This is an important extension, since, as noted by Kattan and Cooper (1998), when discussing computer-based decision techniques in a corporate failure setting, ‘In real world decision making, the patterns of classes often overlap, suggesting that predictor information may be incomplete. … This lack of information results in probabilistic decision making, where perfect prediction accuracy is not expected’.

Relative to the traditional rough set approach, VPRS has the additional desirable property of allowing for partial classification compared to the complete classification required by RST. More specifically, when an object is classified using RST it ...

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