Rough Sets and Knowledge Discovery: An Overview

摘要: The primary methodological framework to study classification problems with imprecise or incomplete information in this book is the theory of rough sets. was originally introduced by Pawlak[1]. uniqueness as well complementary character set other approaches for dealing imprecise, noisy, such fuzzy theory[4], evidence[5] recognized mathematicians and researchers working on mathematical foundations Computer Science. Currently, there are over 800 publications area, including two books an annual workshop. sets model used a departure point formal reasoning uncertain information[6–8], machine learning, knowledge discovery[9–13, 20], representation about knowledge[6]. has been applied numerous domains as, example, analysis clinical data medical diagnosis[14], retrieval[15], control algorithm acquisition process control[16], complex chemical compounds[17], structural engineering[18], market analysis[12], others[9].