Data streams mining have become a novel research topic of growing interest in knowledge
discovery. The data streams which are generated from applications, such as network …

Mining data streams is the process of extracting information from non-stopping, rapidly
flowing data records to provide knowledge that is reliable and timely. Streaming data …

Evolving fuzzy rule-based systems are very powerful methods for online classification of
data streams. In these systems, the classifier is updated by generating, removing and …

The interest in data stream mining is continuously growing due to the increasing volume of
data arriving at high speed produced by various systems. Processing and classification to …

Classification plays a crucial role in mining the evolving data streams. The concept drift and
concept evolution are the major issues of data streams classification, which greatly affect the …

Abstract Analysis of data streams is becoming a key area of data mining research, as the
number of applications demanding such processing increases. Modern information …

A data stream is giant amount of data which is generated uncontrollably at a rapid rate from
many applications like call detail records, log records, sensors applications etc. Data stream …

In Recent years data stream classification has been an extensively studied research
problem. Data streams are continuous and rapid flow of data. Data streams include Call …

In data stream mining, one of the biggest challenges is to develop algorithms that deal with
the changing data. As data evolve over time, static models become outdated. This …

Abstract Concept Drift is considered a challenging problem that appears in data streaming.
The classifier's error rate and the ensemble are used in most of the previous works to …