Abstract Machine learning and data mining rely on feature selection to reduce the dimension
of data and increase the performance of algorithms. As a result of such a large search …

Spatial autocorrelation, of which Geary'sc has traditionally been a popular measure, is
fundamental to spatial science. This paper provides a new perspective on Geary'sc. We …

Semi-supervised regression aims to improve the performance of the learner with the help of
unlabeled data. Popular approaches select some unlabeled data with high-quality pseudo …

Due to the rapid growth of the internet, there are more and more graph-structured datasets
such as social networks, co-purchase graphs, citation networks, and so on. The combination …

The contribution exposes and illustrates a general, flexible formalism, together with an
associated iterative procedure, aimed at determining soft memberships of marked nodes in …

A large number of features is the main problem in big data, leading to the curse of
dimensionality. Meanwhile, feature selection is suggested as a solution. The process of …