Ensemble-based methods are among the most widely used techniques for data stream
classification. Their popularity is attributable to their good performance in comparison to …

The Internet of Things (IoT) is the result of the convergence of sensing, computing, and
networking technologies, allowing devices of varying sizes and computational capabilities …

Current paradigms such as the Internet of Things (IoT) and cyber-physical systems are
transforming production environments, where related processes are not only faster and with …

Machine learning has traditionally been solely performed on servers and high-performance
machines. However, advances in chip technology have given us miniature libraries that fit in …

Sensor networks consist of distributed autonomous devices that cooperatively monitor an
environment. Sensors are equipped with capacities to store information in memory, process …

Recently, data management and processing for wireless sensor networks (WSNs) has
become a topic of active research in several fields of computer science, such as the …

In this paper we propose a new approach for designing an ensemble applied to stream data
classification. Our approach is supported by two theorems showing how to decide whether a …

Modern information technology allows information to be collected at a far greater rate than
ever before. So fast, in fact, that the main problem is making sense of it all. Machine learning …

Data mining is concerned with the process of computationally extracting hidden knowledge
structures represented in models and patterns from large data repositories. It is an …

In this article, we review the state‐of‐the‐art techniques in mining data streams for mobile
and ubiquitous environments. We start the review with a concise background of data stream …