In this paper, we address the issue of learning nonlinearly separable concepts with a kernel classifier in the situation where the data at hand are altered by a uniform classific...
Random projection is a simple technique that has had a number of applications in algorithm design. In the context of machine learning, it can provide insight into questions such as...
This paper proposes a model-driven, extensible platform, delivered on the Web, which is able to support long-distance collaboration of students’ teams working on complex projects...
WEKA is a popular machine learning workbench with a development life of nearly two decades. This article provides an overview of the factors that we believe to be important to its...
Remco R. Bouckaert, Eibe Frank, Mark A. Hall, Geof...
We investigate how random projection can best be used for clustering high dimensional data. Random projection has been shown to have promising theoretical properties. In practice,...