Parallel Coordinates

Visual Multidimensional Geometry and Its Applications
 Book,CDROM
Sofort lieferbar | Lieferzeit:3-5 Tage I
ISBN-13:
9780387215075
Einband:
Book,CDROM
Erscheinungsdatum:
08.10.2009
Seiten:
554
Autor:
Alfred Inselberg
Gewicht:
1297 g
Format:
242x187x37 mm
Sprache:
Englisch
Beschreibung:

This book is about visualization, and systematically incorporating the fantastic human pattern recognition into the problem-solving process. Focusing on parallel coordinates, it contains numerous exercises with solutions, course projects and research directions.
Parallel coordinates has emerged as the leading methodology for multidimensional visualization. Starting from the geometrical foundations, here is a systematic and rigorous exposition of the methodology's mathematical and algorithmic components. Exercises range from the basics to advanced project topics and open research questions. This book provides the only text to build theory from the foundations of projective geometry, giving readers a deeper understanding of the material.
Foreword.- Preface.- Introduction.- Geometry Background.- The Plane with Parallel Coordinates.- Multidimensional Lines.- Hyperplanes and p-Flats RN.- Envelopes.- Curves.- Proximity of Lines, Planes, and Flats.- Hypersurfaces in RN.- Data Mining and Other Applications.- Recent Results.- Solutions to Selected Exercises.- Notation and List of Symbols.- Bibliography.- Index.
This is one book that can genuinely be said to be straight from the horse's mouth. Written by the originator of the technique, it examines parallel coordinates as the leading methodology for multidimensional visualization. Starting from geometric foundations, this is the first systematic and rigorous exposition of the methodology's mathematical and algorithmic components. It covers, among many others, the visualization of multidimensional lines, minimum distances, planes, hyperplanes, and clusters of "near" planes. The last chapter explains in a non-technical way the methodology's application to visual and automatic data mining. The principles of the latter, along with guidelines, strategies and algorithms are illustrated in detail on real high-dimensional datasets.

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