In this research we present a novel approach to the concept change detection problem.
Change detection is a fundamental issue with data stream mining as classification models …

In this research we present a novel approach to the concept change detection problem.
Change detection is a fundamental issue with data stream mining as models generated …

Imperfect data stream leads to tree size explosion and detrimental accuracy problems.
Overfitting problem and the imbalanced class distribution reduce the performance of the …

Most existing model-based approaches to anomaly detection in streaming data are based
on decision trees due to their fast construction speed [1]. This paper proposes two fast …

In this research, we apply ensembles of Fourier encoded spectra to capture and mine
recurring concepts in a data stream environment. Previous research showed that compact …

In this research we address the problem of capturing recurring concepts in a data stream
environment. Recurrence capture enables the re-use of previously learned classifiers …

Large volume of high-speed streaming data is generated by big power grids continuously. In
order to detect and avoid power grid failure, decision support systems (DSSs) are commonly …

Big data is a popular topic that attracts highly attentions of researchers from all over the
world. How to mine valuable information from such huge volumes of data remains an open …

The two-volume set LNAI 7818+ LNAI 7819 constitutes the refereed proceedings of the 17th
Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2013, held in …

Decision tree, as one of the most widely used methods in data mining, has been used in
many realistic applications. Incremental decision tree handles streaming data scenario that …