The identification of network attacks which target information and communication systems
has been a focus of the research community for years. Network intrusion detection is a …

k nearest neighbor (kNN) is a simple and widely used classifier; it can achieve comparable
performance with more complex classifiers including decision tree and artificial neural …

With atmospheric environmental pollution becoming increasingly serious, developing an
early warning system for air quality forecasting is vital to monitoring and controlling air …

Bridges are one of the critical infrastructure systems and play a critical role in supporting the
economic development of nations. During the planning, design, and construction phases of …

Data stream mining, as its name suggests, is connected with two basic fields of computer
science, ie data mining and data streams. Data mining [1–4] is an interdisciplinary subfield …

Data preprocessing is known to be essential to produce accurate data from which mining
methods are able to extract valuable knowledge. When data constantly arrives from one or …

This paper proposes a novel algorithm for incremental learning over streaming data in a non-
stationary environment. The idea refers to the applicability of Probabilistic Neural Networks …

Probabilistic label learning is a challenging task that arises from recent real-world problems
within the weakly supervised classification framework. In this task algorithms have to deal …

In the machine learning literature we can find numerous methods to solve classification
problems. We propose two new performance measures to analyze such methods. These …

An experiment was conducted to investigate the effect of the inconsistency rate (IR) of
granulated datasets on classification performance. Unsupervised (equal-width interval, EWI) …