Regression is one of the most important supervised learning methods in data mining that is
used to predict and discover knowledge in data mining science. After reviewing the studies …

Regular prices and temporary discounts are important elements for retailers' and brands'
pricing decisions. These two variables need to be considered separately because consumer …

Multiple structural breaks detection for Interval-Valued Time Series (IVTS) is undoubtedly
relevant under practical perspectives and challenging under the point of view of the analysis …

This article introduces a clustering approach to roadway segment division, in place of the
traditional fixed-length and variable-length division methods, to improve the calibration of …

Ever since HE Hurst brought the concept of long memory time series to prominence in his
study of river flows the origins of the so-called Hurst phenomena have remained elusive …

The aim of this paper is to conduct change point analysis of interval-valued time series
employing a regression trees approach. In order to deal with such time series we propose to …

The task identifying changes and irregularities in medical insurance claim payments is a
difficult process of which the traditional practice involves querying historical claims …

In dieser Arbeit wird analysiert, ob die durch Ad-hoc-Meldungen ausgelösten
Kapitalmarktreaktionen mit traditionellen Finanzmarkttheorien oder mit Aspekten der …

In this paper we describe how to conduct a change-point analysis when dealing with time
series imprecisely or vaguely observed, ie time ordered observations whose values are not …

We propose a recursive partitioning approach to identify groups of risky financial institutions
using a synthetic indicator built on the information arising from a sample of pooled systemic …