Abstract
In this work we present an integrated set of tools allowing a multi-step process that, starting from raw datasets, brings them through dimensionality reduction, preclustering analysis and clustering assessment, to a visual and interactive environment for data exploration. At the core of the process lies the idea of subdividing the process of data clusterization into different steps: a preliminary analysis in which algorithmic parameters are estimated, a clustering step based on the previous analysis and, finally, a clusterization assessment step including interactive clustering. This last step allows users to participate in the process of clustering and helps them figuring out the data underlying structures. The models are actually implemented in a group of integrated, user-friendly tools under the MATLAB environment, featuring a number of classical and novel data processing, visualization, assessment and interaction methods.