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Advances in data science : symbolic, complex, and network data / / edited by Edwin Diday, Rong Guan, Gilbert Saporta, Huiwen Wang
| Advances in data science : symbolic, complex, and network data / / edited by Edwin Diday, Rong Guan, Gilbert Saporta, Huiwen Wang |
| Autore | Diday Edwin |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | London, England ; ; Hoboken, New Jersey : , : ISTE : , : Wiley, , [2020] |
| Descrizione fisica | 1 online resource (253 pages) |
| Disciplina | 006.312 |
| Collana | Big data, artificial intelligence and data analysis set |
| Soggetto topico |
Data mining
Quantitative research |
| ISBN |
1-119-69510-4
1-119-69511-2 1-119-69496-5 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910554802503321 |
Diday Edwin
|
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| London, England ; ; Hoboken, New Jersey : , : ISTE : , : Wiley, , [2020] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Clustering methodology for symbolic data / / Lynne Billard (University of Georgia), Edwin Diday (Universite de Paris IX--Dauphine)
| Clustering methodology for symbolic data / / Lynne Billard (University of Georgia), Edwin Diday (Universite de Paris IX--Dauphine) |
| Autore | Billard L (Lynne), <1943-> |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , [2020] |
| Descrizione fisica | 1 online resource (351 pages) |
| Disciplina | 519.53 |
| Soggetto topico |
Cluster analysis
Multivariate analysis |
| ISBN |
1-119-01039-X
1-119-01038-1 1-119-01040-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Symbolic data, basics -- Dissimilarity, similarity, and distance measures -- Dissimilarity, similarity, and distance measures, modal data -- General clustering techniques -- Partitioning techniques -- Divisive hierarchical clustering -- Agglomerative hierarchical clustering. |
| Record Nr. | UNINA-9910554805903321 |
|
Billard L (Lynne), <1943->
|
||
| Hoboken, New Jersey : , : Wiley, , [2020] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Clustering methodology for symbolic data / / Lynne Billard (University of Georgia), Edwin Diday (Universite de Paris IX--Dauphine)
| Clustering methodology for symbolic data / / Lynne Billard (University of Georgia), Edwin Diday (Universite de Paris IX--Dauphine) |
| Autore | Billard L (Lynne), <1943-> |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , [2020] |
| Descrizione fisica | 1 online resource (351 pages) |
| Disciplina | 519.53 |
| Soggetto topico |
Cluster analysis
Multivariate analysis |
| ISBN |
1-119-01039-X
1-119-01038-1 1-119-01040-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Symbolic data, basics -- Dissimilarity, similarity, and distance measures -- Dissimilarity, similarity, and distance measures, modal data -- General clustering techniques -- Partitioning techniques -- Divisive hierarchical clustering -- Agglomerative hierarchical clustering. |
| Record Nr. | UNINA-9910814409603321 |
|
Billard L (Lynne), <1943->
|
||
| Hoboken, New Jersey : , : Wiley, , [2020] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Symbolic data analysis [[electronic resource] ] : conceptual statistics and data mining / / Lynne Billard, Edwin Diday
| Symbolic data analysis [[electronic resource] ] : conceptual statistics and data mining / / Lynne Billard, Edwin Diday |
| Autore | Billard L (Lynne), <1943-> |
| Pubbl/distr/stampa | Chichester, England ; ; Hoboken, NJ, : John Wiley & Sons Inc., c2006 |
| Descrizione fisica | 1 online resource (331 p.) |
| Disciplina |
519.5/35
519.535 |
| Altri autori (Persone) | DidayE |
| Collana |
Wiley Series in Computational Statistics
Wiley series in computational statistics |
| Soggetto topico |
Data mining
Multivariate analysis |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-280-59231-1
9786613622143 0-470-09018-9 0-470-09017-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Symbolic Data Analysis; Contents; 1 Introduction; References; 2 Symbolic Data; 2.1 Symbolic and Classical Data; 2.1.1 Types of data; 2.1.2 Dependencies in the data; 2.2 Categories, Concepts, and Symbolic Objects; 2.2.1 Preliminaries; 2.2.2 Descriptions, assertions, extents; 2.2.3 Concepts of concepts; 2.2.4 Some philosophical aspects; 2.2.5 Fuzzy, imprecise, and conjunctive data; 2.3 Comparison of Symbolic and Classical Analyses; Exercises; References; 3 Basic Descriptive Statistics: One Variate; 3.1 Some Preliminaries; 3.2 Multi-Valued Variables; 3.3 Interval-Valued Variables
3.4 Modal Multi-Valued Variables3.5 Modal Interval-Valued Variables; Exercises; References; 4 Descriptive Statistics: Two or More Variates; 4.1 Multi-Valued Variables; 4.2 Interval-Valued Variables; 4.3 Modal Multi-Valued Variables; 4.4 Modal Interval-Valued Variables; 4.5 Baseball Interval-Valued Dataset; 4.5.1 The data: actual and virtual datasets; 4.5.2 Joint histograms; 4.5.3 Guiding principles; 4.6 Measures of Dependence; 4.6.1 Moment dependence; 4.6.2 Spearman's rho and copulas; Exercises; References; 5 Principal Component Analysis; 5.1 Vertices Method; 5.2 Centers Method 5.3 Comparison of the MethodsExercises; References; 6 Regression Analysis; 6.1 Classical Multiple Regression Model; 6.2 Multi-Valued Variables; 6.2.1 Single dependent variable; 6.2.2 Multi-valued dependent variable; 6.3 Interval-Valued Variables; 6.4 Histogram-Valued Variables; 6.5 Taxonomy Variables; 6.6 Hierarchical Variables; Exercises; References; 7 Cluster Analysis; 7.1 Dissimilarity and Distance Measures; 7.1.1 Basic definitions; 7.1.2 Multi-valued variables; 7.1.3 Interval-valued variables; 7.1.4 Mixed-valued variables; 7.2 Clustering Structures; 7.2.1 Types of clusters: definitions 7.2.2 Construction of clusters: building algorithms7.3 Partitions; 7.4 Hierarchy-Divisive Clustering; 7.4.1 Some basics; 7.4.2 Multi-valued variables; 7.4.3 Interval-valued variables; 7.5 Hierarchy-Pyramid Clusters; 7.5.1 Some basics; 7.5.2 Comparison of hierarchy and pyramid structures; 7.5.3 Construction of pyramids; Exercises; References; Data Index; Author Index; Subject Index |
| Record Nr. | UNINA-9910144714603321 |
|
Billard L (Lynne), <1943->
|
||
| Chichester, England ; ; Hoboken, NJ, : John Wiley & Sons Inc., c2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Symbolic data analysis [[electronic resource] ] : conceptual statistics and data mining / / Lynne Billard, Edwin Diday
| Symbolic data analysis [[electronic resource] ] : conceptual statistics and data mining / / Lynne Billard, Edwin Diday |
| Autore | Billard L (Lynne), <1943-> |
| Pubbl/distr/stampa | Chichester, England ; ; Hoboken, NJ, : John Wiley & Sons Inc., c2006 |
| Descrizione fisica | 1 online resource (331 p.) |
| Disciplina |
519.5/35
519.535 |
| Altri autori (Persone) | DidayE |
| Collana |
Wiley Series in Computational Statistics
Wiley series in computational statistics |
| Soggetto topico |
Data mining
Multivariate analysis |
| ISBN |
1-280-59231-1
9786613622143 0-470-09018-9 0-470-09017-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Symbolic Data Analysis; Contents; 1 Introduction; References; 2 Symbolic Data; 2.1 Symbolic and Classical Data; 2.1.1 Types of data; 2.1.2 Dependencies in the data; 2.2 Categories, Concepts, and Symbolic Objects; 2.2.1 Preliminaries; 2.2.2 Descriptions, assertions, extents; 2.2.3 Concepts of concepts; 2.2.4 Some philosophical aspects; 2.2.5 Fuzzy, imprecise, and conjunctive data; 2.3 Comparison of Symbolic and Classical Analyses; Exercises; References; 3 Basic Descriptive Statistics: One Variate; 3.1 Some Preliminaries; 3.2 Multi-Valued Variables; 3.3 Interval-Valued Variables
3.4 Modal Multi-Valued Variables3.5 Modal Interval-Valued Variables; Exercises; References; 4 Descriptive Statistics: Two or More Variates; 4.1 Multi-Valued Variables; 4.2 Interval-Valued Variables; 4.3 Modal Multi-Valued Variables; 4.4 Modal Interval-Valued Variables; 4.5 Baseball Interval-Valued Dataset; 4.5.1 The data: actual and virtual datasets; 4.5.2 Joint histograms; 4.5.3 Guiding principles; 4.6 Measures of Dependence; 4.6.1 Moment dependence; 4.6.2 Spearman's rho and copulas; Exercises; References; 5 Principal Component Analysis; 5.1 Vertices Method; 5.2 Centers Method 5.3 Comparison of the MethodsExercises; References; 6 Regression Analysis; 6.1 Classical Multiple Regression Model; 6.2 Multi-Valued Variables; 6.2.1 Single dependent variable; 6.2.2 Multi-valued dependent variable; 6.3 Interval-Valued Variables; 6.4 Histogram-Valued Variables; 6.5 Taxonomy Variables; 6.6 Hierarchical Variables; Exercises; References; 7 Cluster Analysis; 7.1 Dissimilarity and Distance Measures; 7.1.1 Basic definitions; 7.1.2 Multi-valued variables; 7.1.3 Interval-valued variables; 7.1.4 Mixed-valued variables; 7.2 Clustering Structures; 7.2.1 Types of clusters: definitions 7.2.2 Construction of clusters: building algorithms7.3 Partitions; 7.4 Hierarchy-Divisive Clustering; 7.4.1 Some basics; 7.4.2 Multi-valued variables; 7.4.3 Interval-valued variables; 7.5 Hierarchy-Pyramid Clusters; 7.5.1 Some basics; 7.5.2 Comparison of hierarchy and pyramid structures; 7.5.3 Construction of pyramids; Exercises; References; Data Index; Author Index; Subject Index |
| Record Nr. | UNINA-9910829933903321 |
|
Billard L (Lynne), <1943->
|
||
| Chichester, England ; ; Hoboken, NJ, : John Wiley & Sons Inc., c2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Symbolic data analysis : conceptual statistics and data mining / / Lynne Billard, Edwin Diday
| Symbolic data analysis : conceptual statistics and data mining / / Lynne Billard, Edwin Diday |
| Autore | Billard L (Lynne), <1943-> |
| Pubbl/distr/stampa | Chichester, England ; ; Hoboken, NJ, : John Wiley & Sons Inc., c2006 |
| Descrizione fisica | 1 online resource (331 p.) |
| Disciplina |
519.5/35
519.535 |
| Altri autori (Persone) | DidayE |
| Collana | Wiley series in computational statistics |
| Soggetto topico |
Data mining
Multivariate analysis |
| ISBN |
1-280-59231-1
9786613622143 0-470-09018-9 0-470-09017-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Symbolic Data Analysis; Contents; 1 Introduction; References; 2 Symbolic Data; 2.1 Symbolic and Classical Data; 2.1.1 Types of data; 2.1.2 Dependencies in the data; 2.2 Categories, Concepts, and Symbolic Objects; 2.2.1 Preliminaries; 2.2.2 Descriptions, assertions, extents; 2.2.3 Concepts of concepts; 2.2.4 Some philosophical aspects; 2.2.5 Fuzzy, imprecise, and conjunctive data; 2.3 Comparison of Symbolic and Classical Analyses; Exercises; References; 3 Basic Descriptive Statistics: One Variate; 3.1 Some Preliminaries; 3.2 Multi-Valued Variables; 3.3 Interval-Valued Variables
3.4 Modal Multi-Valued Variables3.5 Modal Interval-Valued Variables; Exercises; References; 4 Descriptive Statistics: Two or More Variates; 4.1 Multi-Valued Variables; 4.2 Interval-Valued Variables; 4.3 Modal Multi-Valued Variables; 4.4 Modal Interval-Valued Variables; 4.5 Baseball Interval-Valued Dataset; 4.5.1 The data: actual and virtual datasets; 4.5.2 Joint histograms; 4.5.3 Guiding principles; 4.6 Measures of Dependence; 4.6.1 Moment dependence; 4.6.2 Spearman's rho and copulas; Exercises; References; 5 Principal Component Analysis; 5.1 Vertices Method; 5.2 Centers Method 5.3 Comparison of the MethodsExercises; References; 6 Regression Analysis; 6.1 Classical Multiple Regression Model; 6.2 Multi-Valued Variables; 6.2.1 Single dependent variable; 6.2.2 Multi-valued dependent variable; 6.3 Interval-Valued Variables; 6.4 Histogram-Valued Variables; 6.5 Taxonomy Variables; 6.6 Hierarchical Variables; Exercises; References; 7 Cluster Analysis; 7.1 Dissimilarity and Distance Measures; 7.1.1 Basic definitions; 7.1.2 Multi-valued variables; 7.1.3 Interval-valued variables; 7.1.4 Mixed-valued variables; 7.2 Clustering Structures; 7.2.1 Types of clusters: definitions 7.2.2 Construction of clusters: building algorithms7.3 Partitions; 7.4 Hierarchy-Divisive Clustering; 7.4.1 Some basics; 7.4.2 Multi-valued variables; 7.4.3 Interval-valued variables; 7.5 Hierarchy-Pyramid Clusters; 7.5.1 Some basics; 7.5.2 Comparison of hierarchy and pyramid structures; 7.5.3 Construction of pyramids; Exercises; References; Data Index; Author Index; Subject Index |
| Record Nr. | UNINA-9910877002803321 |
|
Billard L (Lynne), <1943->
|
||
| Chichester, England ; ; Hoboken, NJ, : John Wiley & Sons Inc., c2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Symbolic data analysis and the SODAS software [[electronic resource] /] / edited by Edwin Diday, Monique Noirhomme-Fraiture
| Symbolic data analysis and the SODAS software [[electronic resource] /] / edited by Edwin Diday, Monique Noirhomme-Fraiture |
| Pubbl/distr/stampa | Chichester, England ; ; Hoboken, NJ, : J. Wiley & Sons, c2008 |
| Descrizione fisica | 1 online resource (477 p.) |
| Disciplina |
005.74
519.535 |
| Altri autori (Persone) |
DidayE
Noirhomme-FraitureMonique |
| Soggetto topico | Data mining |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-281-30833-1
9786611308339 0-470-72356-4 0-470-72355-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Symbolic Data Analysis and the SODAS Software; Contents; Contributors; Foreword; Preface; ASSO Partners; Introduction; 1 The state of the art in symbolic data analysis: overview and future; Part I Databases versus Symbolic Objects; 2 Improved generation of symbolic objects from relational databases; 3 Exporting symbolic objects to databases; 4 A statistical metadata model for symbolic objects; 5 Editing symbolic data; 6 The normal symbolic form; 7 Visualization; Part II Unsupervised Methods; 8 Dissimilarity and matching; 9 Unsupervised divisive classification
10 Hierarchical and pyramidal clustering11 Clustering methods in symbolic data analysis; 12 Visualizing symbolic data by Kohonen maps; 13 Validation of clustering structure: determination of the number of clusters; 14 Stability measures for assessing a partition and its clusters: application to symbolic data sets; 15 Principal component analysis of symbolic data described by intervals; 16 Generalized canonical analysis; Part III Supervised Methods; 17 Bayesian decision trees; 18 Factor discriminant analysis; 19 Symbolic linear regression methodology 20 Multi-layer perceptrons and symbolic dataPart IV Applications and the SODAS Software; 21 Application to the Finnish, Spanish and Portuguese data of the European Social Survey; 22 People's life values and trust components in Europe: symbolic data analysis for 20-22 countries; 23 Symbolic analysis of the Time Use Survey in the Basque country; 24 SODAS2 software: Overview and methodology; Index |
| Record Nr. | UNINA-9910144713103321 |
| Chichester, England ; ; Hoboken, NJ, : J. Wiley & Sons, c2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Symbolic data analysis and the SODAS software [[electronic resource] /] / edited by Edwin Diday, Monique Noirhomme-Fraiture
| Symbolic data analysis and the SODAS software [[electronic resource] /] / edited by Edwin Diday, Monique Noirhomme-Fraiture |
| Pubbl/distr/stampa | Chichester, England ; ; Hoboken, NJ, : J. Wiley & Sons, c2008 |
| Descrizione fisica | 1 online resource (477 p.) |
| Disciplina |
005.74
519.535 |
| Altri autori (Persone) |
DidayE
Noirhomme-FraitureMonique |
| Soggetto topico | Data mining |
| ISBN |
1-281-30833-1
9786611308339 0-470-72356-4 0-470-72355-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Symbolic Data Analysis and the SODAS Software; Contents; Contributors; Foreword; Preface; ASSO Partners; Introduction; 1 The state of the art in symbolic data analysis: overview and future; Part I Databases versus Symbolic Objects; 2 Improved generation of symbolic objects from relational databases; 3 Exporting symbolic objects to databases; 4 A statistical metadata model for symbolic objects; 5 Editing symbolic data; 6 The normal symbolic form; 7 Visualization; Part II Unsupervised Methods; 8 Dissimilarity and matching; 9 Unsupervised divisive classification
10 Hierarchical and pyramidal clustering11 Clustering methods in symbolic data analysis; 12 Visualizing symbolic data by Kohonen maps; 13 Validation of clustering structure: determination of the number of clusters; 14 Stability measures for assessing a partition and its clusters: application to symbolic data sets; 15 Principal component analysis of symbolic data described by intervals; 16 Generalized canonical analysis; Part III Supervised Methods; 17 Bayesian decision trees; 18 Factor discriminant analysis; 19 Symbolic linear regression methodology 20 Multi-layer perceptrons and symbolic dataPart IV Applications and the SODAS Software; 21 Application to the Finnish, Spanish and Portuguese data of the European Social Survey; 22 People's life values and trust components in Europe: symbolic data analysis for 20-22 countries; 23 Symbolic analysis of the Time Use Survey in the Basque country; 24 SODAS2 software: Overview and methodology; Index |
| Record Nr. | UNINA-9910831069403321 |
| Chichester, England ; ; Hoboken, NJ, : J. Wiley & Sons, c2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Symbolic data analysis and the SODAS software / / edited by Edwin Diday, Monique Noirhomme-Fraiture
| Symbolic data analysis and the SODAS software / / edited by Edwin Diday, Monique Noirhomme-Fraiture |
| Pubbl/distr/stampa | Chichester, England ; ; Hoboken, NJ, : J. Wiley & Sons, c2008 |
| Descrizione fisica | 1 online resource (477 p.) |
| Disciplina | 005.74 |
| Altri autori (Persone) |
DidayE
Noirhomme-FraitureMonique |
| Soggetto topico | Data mining |
| ISBN |
1-281-30833-1
9786611308339 0-470-72356-4 0-470-72355-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Symbolic Data Analysis and the SODAS Software; Contents; Contributors; Foreword; Preface; ASSO Partners; Introduction; 1 The state of the art in symbolic data analysis: overview and future; Part I Databases versus Symbolic Objects; 2 Improved generation of symbolic objects from relational databases; 3 Exporting symbolic objects to databases; 4 A statistical metadata model for symbolic objects; 5 Editing symbolic data; 6 The normal symbolic form; 7 Visualization; Part II Unsupervised Methods; 8 Dissimilarity and matching; 9 Unsupervised divisive classification
10 Hierarchical and pyramidal clustering11 Clustering methods in symbolic data analysis; 12 Visualizing symbolic data by Kohonen maps; 13 Validation of clustering structure: determination of the number of clusters; 14 Stability measures for assessing a partition and its clusters: application to symbolic data sets; 15 Principal component analysis of symbolic data described by intervals; 16 Generalized canonical analysis; Part III Supervised Methods; 17 Bayesian decision trees; 18 Factor discriminant analysis; 19 Symbolic linear regression methodology 20 Multi-layer perceptrons and symbolic dataPart IV Applications and the SODAS Software; 21 Application to the Finnish, Spanish and Portuguese data of the European Social Survey; 22 People's life values and trust components in Europe: symbolic data analysis for 20-22 countries; 23 Symbolic analysis of the Time Use Survey in the Basque country; 24 SODAS2 software: Overview and methodology; Index |
| Record Nr. | UNINA-9910877870403321 |
| Chichester, England ; ; Hoboken, NJ, : J. Wiley & Sons, c2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||