Data analysis is changing fast. Driven by a vast range of application domains and affordable tools, machine learning has become mainstream. Unsupervised data analysis, including cluster analysis, factor analysis, and low dimensionality mapping methods continually being updated, have reached new heights of achievement in the incredibly rich data wor

part I|2 pages

I Statistical and Machine Learning

part II|2 pages

II Data Science, Foundations, and Applications

chapter 8|12 pages

Semantics from Narrative: State of the Art and Future Prospects

ByFionn Murtagh, Adam Ganz, Joe Reddington

chapter 10|12 pages

A Clustering Approach to Monitor System Working: An Application to Electric Power Production

ByAlzennyr Da Silva, Yves Lechevallier, Redouane Seraoui

chapter 11|10 pages

Introduction to Molecular Phylogeny

ByMahendra Mariadassou, Avner Bar-Hen

chapter 12|12 pages

Bayesian Analysis of Structural Equation Models Using Parameter Expansion

BySéverine Demeyer, Jean-Louis Foulley, Nicolas Fischer, Gilbert Saporta

part III|2 pages

III Complex Data

chapter 13|10 pages

Clustering Trajectories of a Three-Way Longitudinal Dataset

ByMireille Gettler Summa, Bernard Goldfarb, Maurizio Vichi

chapter 15|18 pages

Synthesis of Objects

ByMyriam Touati, Mohamed Djedour, Edwin Diday

chapter 16|8 pages

Functional Data Analysis: An Interdisciplinary Statistical Topic

ByLaurent Delsol, Frédéric Ferraty, Adela Martínez Calvo

chapter 17|8 pages

Methodological Richness of Functional Data Analysis

ByWenceslao Gonzàlez Manteiga, Philippe Vieu