Statistical learning and data science

by Summa, Mireille Gettler

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Title Statements

Full title :Statistical learning and data science / edited by Mireille Gettler Summa [and others].

Summary

"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 world that we inhabit. Statistical Learning and Data Science is a work of reference in the rapidly evolving context of converging methodologies. It gathers contributions from some of the foundational thinkers in the different fields of data analysis to the major theoretical results in the domain. On the methodological front, the volume includes conformal prediction and frameworks for assessing confidence in outputs, together with attendant risk. It illustrates a wide range of applications, including semantics, credit risk, energy production, genomics, and ecology. The book also addresses issues of origin and evolutions in the unsupervised data analysis arena, and presents some approaches for time series, symbolic data, and functional data. Over the history of multidimensional data analysis, more and more complex data have become available for processing. Supervised machine learning, semi-supervised analysis approaches, and unsupervised data analysis, provide great capability for addressing the digital data deluge. Exploring the foundations and recent breakthroughs in the field, Statistical Learning and Data Science demonstrates how data analysis can improve personal and collective health and the well-being of our social, business, and physical environments."--

Edition Statements

Publication Date:©2012.

Publication Statements

Publisher(s):CRC Press
Place of Publication:Boca Raton
Language:eng
Publication Date:©2012.

The Physical Object

Description:xv, 227 pages : : color illustrations ; : 27 cm.

Edition Identifiers

ISBN:9781439867631, 1439867631
oclc:ocn703209011
LC Classification:Q325.5
Dewey Decimal:006.3/1

Mining on social networks / Benjamin Chapus [and others] -- Large-scale machine learning with stochastic gradient descent / Léon Bottou -- Fast optimization algorithms for solving SVM+ / Dmitry Pechyony and Vladimir Vapnik -- Conformal predictors in semisupervised case / Dmitry Adamskiy, Ilia Nouretdinov, and Alexander Gammerman -- Some properties of infinite VC-dimension systems / Alexey Chervonenkis -- Choriogenesis: the dynamical genesis of space and its dimensions, controlled by correspondence analysis / Jean-Paul Benzécri -- Geometric data analysis in a social science research program: the case of Bourdieu's sociology / Frédéric Lebaron -- Semantics from narrative: state of the art and future prospects / Fionn Murtagh, Adam Ganz, and Joe Reddington -- Measuring classifier performance: on the incoherence of the area under the ROC curve and what to do about it / David J. Hand -- A clustering approach to monitor system working: an application to electric power production / Alzennyr Da Silva, Yves Lechevallier, and Redouane Seraoui -- Introduction to molecular phylogeny / Mahendra Mariadassou and Avner Bar-Hen -- Bayesian analysis of structural equation models using parameter exp…

Subjects

Apprentissage automatique -- Méthodes s… BUSINESS & ECONOMICS -- Statistics COMPUTERS -- Machine Theory Data Mining Exploration de données (Informatique) Machine learning -- Statistical methods MATHEMATICS -- Probability & Statistics