Metabolomics research has recently gained popularity because it enables the study of
biological traits at the biochemical level and, as a result, can directly reveal what occurs in a …

Functional data analysis (FDA) is a statistical framework that allows for the analysis of
curves, images, or functions on higher dimensional domains. The goals of FDA, such as …

We explore the framework of permutation-based p-values for assessing the performance of
classifiers. In this paper we study two simple permutation tests. The first test assess whether …

This book discusses machine learning algorithms, such as artificial neural networks of
different architectures, statistical learning theory, and Support Vector Machines used for the …

Vegetation fires have major impacts on the ecosystem and present a significant threat to
human life. Vegetation fires consists of forest fires, cropland fires, and other vegetation fires …

We show that, in functional data classification problems, perfect asymptotic classification is
often possible, making use of the intrinsic very high dimensional nature of functional data …

In this paper we consider the problems of supervised classification and regression in the
case where attributes and labels are functions: a data is represented by a set of functions …

The selection of grouped variables using the random forest algorithm is considered. First a
new importance measure adapted for groups of variables is proposed. Theoretical insights …

This study investigates the applications of nontraditional models for travel mode choice
modeling, which traditionally has relied on disaggregate discrete choice models such as …

Prior research has shown that greater EEG alpha power (8–13​ Hz) is characteristic of more
creative individuals, and more creative task conditions. The present study investigated the …