A clustering method for very large mixed data sets

Abstract

In developed countries, especially over the last decade, there has been an explosive growth in the capability to generate, collect and use very large data sets. The objects of these data sets could be simultaneously described by quantitative and qualitative attributes. At present, algorithms able to process either very large data sets (in metric spaces) or mixed (qualitative and quantitative) incomplete data (missing value) sets have been developed, but not for very large mixed incomplete data sets. In this paper we introduce a new clustering method named GLC+ to process very large mixed incomplete data sets in order to obtain a partition in connected sets.