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Random graphs for statistical pattern recognition [[electronic resource] /] / David J. Marchette
| Random graphs for statistical pattern recognition [[electronic resource] /] / David J. Marchette |
| Autore | Marchette David J |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2004 |
| Descrizione fisica | 1 online resource (261 p.) |
| Disciplina |
511.5
511/.5 |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Random graphs
Pattern perception - Statistical methods Pattern recognition systems |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-280-27535-9
9786610275359 0-470-34946-8 0-471-72208-1 0-471-72209-X |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Random Graphs for Statistical Pattern Recognition; Contents; Preface; Acknowledgments; 1 Preliminaries; 1.1 Graphs and Digraphs; 1.1.1 Graphs; 1.1.2 Digraphs; 1.1.3 Random Graphs; 1.2 Statistical Pattern Recognition; 1.2.1 Classification; 1.2.2 Curse of Dimensionality; 1.2.3 Clustering; 1.3 Statistical Issues; 1.4 Applications; 1.4.1 Artificial Nose; 1.4.2 Hyperspectral Image; 1.4.3 Gene Expression; 1.5 Further Reading; 2 Computational Geometry; 2.1 Introduction; 2.2 Voronoi Cells and Delaunay Triangularization; 2.2.1 Poisson Voronoi Cells; 2.3 Alpha Hulls; 2.4 Minimum Spanning Trees
2.4.1 Alpha Hulls and the MST2.4.2 Clustering; 2.4.3 Classification Complexity; 2.4.4 Application: Renyi Divergence; 2.4.5 Application: Image Segmentation; 2.5 Further Reading; 3 Neighborhood Graphs; 3.1 Introduction; 3.1.1 Application: Image Processing; 3.2 Nearest-Neighbor Graphs; 3.3 k-Nearest-Neighbor Graphs; 3.3.1 Application: Measures of Association; 3.3.2 Application: Artificial Nose; 3.3.3 Application: Outlier Detection; 3.3.4 Application: Dimensionality Reduction; 3.4 Relative Neighborhood Graphs; 3.5 Gabriel Graphs; 3.5.1 Gabriel Graphs and Alpha Hulls 3.5.2 Application: Nearest-Neighbor Prototypes3.6 Sphere-of-Influence Graphs; 3.7 Sphere-of-Attraction Graphs; 3.8 Other Relatives; 3.9 Asymptotics; 3.10 Further Reading; 4 Class Cover Catch Digraphs; 4.1 Catch Digraphs; 4.1.1 Sphere Digraphs; 4.2 Class Covers; 4.2.1 Basic Definitions; 4.3 Dominating sets; 4.4 Distributional Results for Cn,m-graphs; 4.4.1 Univariate Case; 4.4.2 Multivariate CCCDs; 4.5 Characterizations; 4.6 Scale Dimension; 4.6.1 Application: Latent Class Discovery; 4.7 (a,b) Graphs; 4.8 CCCD Classification; 4.9 Homogeneous CCCDs; 4.10 Vector Quantization 4.11 Random Walk Version4.11.1 Application: Face Detection; 4.12 Further Reading; 5 Cluster Catch Digraphs; 5.1 Basic Definitions; 5.2 Dominating Sets; 5.3 Connected Components; 5.4 Variable Metric Clustering; 6 Computational Methods; 6.1 Introduction; 6.2 Kd- Trees; 6.2.1 Data Structure; 6.2.2 Building the Tree; 6.2.3 Searching the Tree; 6.3 Class Cover Catch Digraphs; 6.4 Cluster Catch Digraphs; 6.5 Voronoi Regions and Delaunay Triangularizations; 6.6 Further Reading; References; Author Index; Subject Index |
| Record Nr. | UNINA-9910146082903321 |
Marchette David J
|
||
| Hoboken, N.J., : Wiley-Interscience, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Random graphs for statistical pattern recognition [[electronic resource] /] / David J. Marchette
| Random graphs for statistical pattern recognition [[electronic resource] /] / David J. Marchette |
| Autore | Marchette David J |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2004 |
| Descrizione fisica | 1 online resource (261 p.) |
| Disciplina |
511.5
511/.5 |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Random graphs
Pattern perception - Statistical methods Pattern recognition systems |
| ISBN |
1-280-27535-9
9786610275359 0-470-34946-8 0-471-72208-1 0-471-72209-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Random Graphs for Statistical Pattern Recognition; Contents; Preface; Acknowledgments; 1 Preliminaries; 1.1 Graphs and Digraphs; 1.1.1 Graphs; 1.1.2 Digraphs; 1.1.3 Random Graphs; 1.2 Statistical Pattern Recognition; 1.2.1 Classification; 1.2.2 Curse of Dimensionality; 1.2.3 Clustering; 1.3 Statistical Issues; 1.4 Applications; 1.4.1 Artificial Nose; 1.4.2 Hyperspectral Image; 1.4.3 Gene Expression; 1.5 Further Reading; 2 Computational Geometry; 2.1 Introduction; 2.2 Voronoi Cells and Delaunay Triangularization; 2.2.1 Poisson Voronoi Cells; 2.3 Alpha Hulls; 2.4 Minimum Spanning Trees
2.4.1 Alpha Hulls and the MST2.4.2 Clustering; 2.4.3 Classification Complexity; 2.4.4 Application: Renyi Divergence; 2.4.5 Application: Image Segmentation; 2.5 Further Reading; 3 Neighborhood Graphs; 3.1 Introduction; 3.1.1 Application: Image Processing; 3.2 Nearest-Neighbor Graphs; 3.3 k-Nearest-Neighbor Graphs; 3.3.1 Application: Measures of Association; 3.3.2 Application: Artificial Nose; 3.3.3 Application: Outlier Detection; 3.3.4 Application: Dimensionality Reduction; 3.4 Relative Neighborhood Graphs; 3.5 Gabriel Graphs; 3.5.1 Gabriel Graphs and Alpha Hulls 3.5.2 Application: Nearest-Neighbor Prototypes3.6 Sphere-of-Influence Graphs; 3.7 Sphere-of-Attraction Graphs; 3.8 Other Relatives; 3.9 Asymptotics; 3.10 Further Reading; 4 Class Cover Catch Digraphs; 4.1 Catch Digraphs; 4.1.1 Sphere Digraphs; 4.2 Class Covers; 4.2.1 Basic Definitions; 4.3 Dominating sets; 4.4 Distributional Results for Cn,m-graphs; 4.4.1 Univariate Case; 4.4.2 Multivariate CCCDs; 4.5 Characterizations; 4.6 Scale Dimension; 4.6.1 Application: Latent Class Discovery; 4.7 (a,b) Graphs; 4.8 CCCD Classification; 4.9 Homogeneous CCCDs; 4.10 Vector Quantization 4.11 Random Walk Version4.11.1 Application: Face Detection; 4.12 Further Reading; 5 Cluster Catch Digraphs; 5.1 Basic Definitions; 5.2 Dominating Sets; 5.3 Connected Components; 5.4 Variable Metric Clustering; 6 Computational Methods; 6.1 Introduction; 6.2 Kd- Trees; 6.2.1 Data Structure; 6.2.2 Building the Tree; 6.2.3 Searching the Tree; 6.3 Class Cover Catch Digraphs; 6.4 Cluster Catch Digraphs; 6.5 Voronoi Regions and Delaunay Triangularizations; 6.6 Further Reading; References; Author Index; Subject Index |
| Record Nr. | UNINA-9910830590103321 |
|
Marchette David J
|
||
| Hoboken, N.J., : Wiley-Interscience, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Random graphs for statistical pattern recognition / / David J. Marchette
| Random graphs for statistical pattern recognition / / David J. Marchette |
| Autore | Marchette David J |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2004 |
| Descrizione fisica | 1 online resource (261 p.) |
| Disciplina | 511/.5 |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Random graphs
Pattern perception - Statistical methods Pattern recognition systems |
| ISBN |
1-280-27535-9
9786610275359 0-470-34946-8 0-471-72208-1 0-471-72209-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Random Graphs for Statistical Pattern Recognition; Contents; Preface; Acknowledgments; 1 Preliminaries; 1.1 Graphs and Digraphs; 1.1.1 Graphs; 1.1.2 Digraphs; 1.1.3 Random Graphs; 1.2 Statistical Pattern Recognition; 1.2.1 Classification; 1.2.2 Curse of Dimensionality; 1.2.3 Clustering; 1.3 Statistical Issues; 1.4 Applications; 1.4.1 Artificial Nose; 1.4.2 Hyperspectral Image; 1.4.3 Gene Expression; 1.5 Further Reading; 2 Computational Geometry; 2.1 Introduction; 2.2 Voronoi Cells and Delaunay Triangularization; 2.2.1 Poisson Voronoi Cells; 2.3 Alpha Hulls; 2.4 Minimum Spanning Trees
2.4.1 Alpha Hulls and the MST2.4.2 Clustering; 2.4.3 Classification Complexity; 2.4.4 Application: Renyi Divergence; 2.4.5 Application: Image Segmentation; 2.5 Further Reading; 3 Neighborhood Graphs; 3.1 Introduction; 3.1.1 Application: Image Processing; 3.2 Nearest-Neighbor Graphs; 3.3 k-Nearest-Neighbor Graphs; 3.3.1 Application: Measures of Association; 3.3.2 Application: Artificial Nose; 3.3.3 Application: Outlier Detection; 3.3.4 Application: Dimensionality Reduction; 3.4 Relative Neighborhood Graphs; 3.5 Gabriel Graphs; 3.5.1 Gabriel Graphs and Alpha Hulls 3.5.2 Application: Nearest-Neighbor Prototypes3.6 Sphere-of-Influence Graphs; 3.7 Sphere-of-Attraction Graphs; 3.8 Other Relatives; 3.9 Asymptotics; 3.10 Further Reading; 4 Class Cover Catch Digraphs; 4.1 Catch Digraphs; 4.1.1 Sphere Digraphs; 4.2 Class Covers; 4.2.1 Basic Definitions; 4.3 Dominating sets; 4.4 Distributional Results for Cn,m-graphs; 4.4.1 Univariate Case; 4.4.2 Multivariate CCCDs; 4.5 Characterizations; 4.6 Scale Dimension; 4.6.1 Application: Latent Class Discovery; 4.7 (a,b) Graphs; 4.8 CCCD Classification; 4.9 Homogeneous CCCDs; 4.10 Vector Quantization 4.11 Random Walk Version4.11.1 Application: Face Detection; 4.12 Further Reading; 5 Cluster Catch Digraphs; 5.1 Basic Definitions; 5.2 Dominating Sets; 5.3 Connected Components; 5.4 Variable Metric Clustering; 6 Computational Methods; 6.1 Introduction; 6.2 Kd- Trees; 6.2.1 Data Structure; 6.2.2 Building the Tree; 6.2.3 Searching the Tree; 6.3 Class Cover Catch Digraphs; 6.4 Cluster Catch Digraphs; 6.5 Voronoi Regions and Delaunay Triangularizations; 6.6 Further Reading; References; Author Index; Subject Index |
| Record Nr. | UNINA-9910877210603321 |
|
Marchette David J
|
||
| Hoboken, N.J., : Wiley-Interscience, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||