A novel statistical maximal information coefficient (MIC) that can detect the nonlinear relationships in large data sets was proposed by Reshef et al. (2011), with emphasis being placed on the equitability, which is a very important concept in data exploration. In this paper, an improved...

Clustering is fundamental for using big data. However, AP (affinity propagation) is not good at non-convex datasets, and the input parameter has a marked impact on DBSCAN (density-based spatial clustering of applications with noise). Moreover, new characteristics such as volume, variety,...