In this work we consider the problem of training a linear classifier by assuming that the number of data is huge (in particular, data may be larger than the memory capacity). We propose to adopt a linear least-squares formulation of the problem and an incremental recursive algorithm which...

Severe constraints imposed by the nature of endless sequences of data collected from unstable phenomena have pushed the understanding and the development of automated analysis strategies, such as data clustering techniques. However, current clustering validation approaches are inadequate to data...