This is a project done as a MSc thesis at INESC TEC, Porto. The purpose is to find correlated subspaces in multi-dimensional datastreams in order to train a concept change detector on each subspace instead of training a single one on the whole space. This principle can naturally be applied for other learning algorithms as well.
For further explanation and documentation, please refer to the thesis document which can be found here.