Discretization of numerical data is one of the most influential data preprocessing tasks in
knowledge discovery and data mining. The purpose of attribute discretization is to find …

Traffic classification groups similar or related traffic data, which is one main stream
technique of data fusion in the field of network management and security. With the rapid …

Data preprocessing is a major and essential stage whose main goal is to obtain final data
sets that can be considered correct and useful for further data mining algorithms. This paper …

DNA microarray technology is the fabrication of a single chip to contain a thousand genetic
codes. Each microarray experiment can analyze many thousands of genes in parallel. The …

Discretization is an essential preprocessing technique used in many knowledge discovery
and data mining tasks. Its main goal is to transform a set of continuous attributes into discrete …

A fuzzy rough set is an important rough set model used for feature selection. It uses the fuzzy
rough dependency as a criterion for feature selection. However, this model can merely …

Rough sets, a tool for data mining, deal with the vagueness and granularity in information
systems. This paper studies covering-based rough sets from the topological view. We …

Rough set theory is a useful tool for data mining. It is based on equivalence relations and
has been extended to covering-based generalized rough set. This paper studies three kinds …

Rough set theory has been proposed by Pawlak as a tool for dealing with the vagueness
and granularity in information systems. The core concepts of classical rough sets are lower …

Substantial recent efforts have been made on the application of Machine Learning (ML)
techniques to flow statistical features for traffic classification. However, the classification …