… the rough set based lazy classification method. The FP-growth algorithm is known as an
efficient and scalable method for frequent pattern discovery from transaction data sets. We …

… rough set methods again such reproaches. We show that some classification methods based
on rough set … scalable. The lazy rule-based classification diagram is presented in Figure 2 …

… The layout of the article is as follows: In Section 2, we remind basic rough set notions and
prove some of their properties that will be applied in the proposed algorithms. In Section 3, we …

… of the theory of rough sets in the domain of data mining and knowledge discovery for big
data. This paper proposes a scalable and effective algorithm based on rough sets for large-…

… rough set algorithms on distributed clusters of commodity computers and speed up big data
analyses. Although a variety of scalable rough set … -art scalable implementations of rough set …

… (2018), can be regarded as a significant contribution to the overall rough set approach in
providing effective, sustainable and scalable methods for large-scale data analysis. It seems …

… In this paper we investigate the scalability features of rough set based methods in the context
of … known scalable methods and present one of the latest scalable rough set classifiers. The …

… selection (FS) methods in terms of their scalability. Although there … The use of fuzzy–rough
set theory (FRS) for the task of … Fuzzy–rough set theory extends the rough set approximation …

… level, as using the whole data set. The natural question for Rough Set Society is does rough
set theory can propose some new and accurate methods for big data. We will present the …

… rough set models, this paper first presents a new rough set model for rough data analysis in
big data, called local rough set, … large-scale data set to verify scalability of the local rough set. …