MDCStream

Abstract

The establishment of modern technological paradigms like ubiquitous computing, big data, cyber-physical systems, or communication networks has strongly increased the need for efficient, effective data stream analysis. MDCStream is a MATLAB tool for generating temporal-dependent numerical datasets in order to stress-test stream data classification, clustering, and outlier detection algorithms. MDCStream is built on MDCGen, therefore showing a high flexibility for creating a wide diversity of data scenarios. To show an example of the potential of MDCStream, we tested a stream data clustering algorithm recently proposed in the literature with datasets generated with MDCStream. Datasets were designed to draw challenges related to space geometries and concept drift.

The establishment of modern technological paradigms like ubiquitous computing, big data, cyber-physical systems, or communication networks has strongly increased the need for efficient, effective data stream analysis. MDCStream is a MATLAB tool for generating temporal-dependent numerical datasets in order to stress-test stream data classification, clustering, and outlier detection algorithms. MDCStream is built on MDCGen, therefore showing a high flexibility for creating a wide diversity of data scenarios. To show an example of the potential of MDCStream, we tested a stream data clustering algorithm recently proposed in the literature with datasets generated with MDCStream. Datasets were designed to draw challenges related to space geometries and concept drift.