A rapid growth of interest in rough set theory [297] and its applications can be lately seen in
the number of international workshops, conferences and seminars that are either directly …

The main statistics used in rough set data analysis, the approximation quality, is of limited
value when there is a choice of competing models for predicting a decision variable. In …

The two-volume set of proceedings of IJCRS 2017, the 2017 International Joint Conference
on Rough Sets, contains the results of the meeting of the International Rough Set Society …

The package RoughSets, written mainly in the R language, provides implementations of
methods from the rough set theory (RST) and fuzzy rough set theory (FRST) for data …

摘要在大数据时代, 如何充分挖掘出蕴藏于数据资源中的价值正在成为各国IT 业界,
学术界和政府共同关注的焦点. 使用云计算平台分布式地存储和分析大数据已经成为共识并且 …

Intrusion detection systems (IDSs) are commonly employed to mitigate network security
threats in various fields, including federated learning applications within the Internet of …

Two attributes $ A $ and $ B $ are said to interact when it helps to observe the attribute
values of both attributes together. This is an example of a $2 $-way interaction. In general, a …

A state-of-the-art review of the literature related to economic and financial prediction using
rough sets model is presented, with special emphasis on the business failure prediction …

This thesis examines how discernibility-based methods can be equipped to posses several
qualities that are needed for analyzing tabular medical data, and how these models can be …

Big data, artificial intelligence and the Internet of things (IoT) are still very popular areas in
current research and industrial applications. Processing massive amounts of data generated …