Parallel coordinates has emerged 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 on the visualization of multidimensional lines, minimum distances, planes, hyperplanes, clusters of "near" planes, proximities, multidimensional transformations, curves, surfaces, hypersurfaces, convexity, and interior-point construction algorithms. The last chapter explains in a non-technical way the methodology's application to visual and automatic data mining with principles, guidelines, strategies and algorithms illustrated in detail on real high-dimensional datasets. Key features: * Systematic presentation of topics interlaced with applications to visual and automatic data mining, collision avoidance algorithms for air traffic control, geometric modeling and computer vision, decision support, information visualization * A large collection of exercises from the basics to advanced project topics and open research questions * Companion text for courses on informational visualization, multivariate statistics, linear algebra, and optimization * Included in a CD, which is designed for interactive classroom use, are visualizations of key topics and examples, coordinated with cross-references in the text * Extensive bibliography on multivariate/multidimensional visualization techniques and excellent index. "Parallel Coordinates" is well-suited for the classroom, as a reference text, or for reference, requiring only a sound foundation in Linear Algebra. — Ce texte fait référence à une édition épuisée ou non disponible de ce titre.