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Advanced Studies in Behaviormetrics and Data Science [[electronic resource] ] : Essays in Honor of Akinori Okada / / edited by Tadashi Imaizumi, Atsuho Nakayama, Satoru Yokoyama
| Advanced Studies in Behaviormetrics and Data Science [[electronic resource] ] : Essays in Honor of Akinori Okada / / edited by Tadashi Imaizumi, Atsuho Nakayama, Satoru Yokoyama |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (XV, 472 p. 136 illus., 69 illus. in color.) |
| Disciplina | 658.8342 |
| Collana | Behaviormetrics: Quantitative Approaches to Human Behavior |
| Soggetto topico |
Statistics
Motivation research (Marketing) Mathematics Visualization Social sciences Psychometrics Statistics for Social Sciences, Humanities, Law Statistical Theory and Methods Consumer Behavior Methodology of the Social Sciences |
| ISBN | 981-15-2700-8 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Co-clustering for object by variable data matrices -- How to use the Hermitian Form Model for asymmetric MDS -- Asymmetric scaling models for square contingency tables: points, circles, arrows, and odds ratios -- Comparing partitions of the Petersen graph -- Minkowski distances and standardisation for clustering and classification on high dimensional data. . |
| Record Nr. | UNISA-996418190803316 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Advanced Studies in Behaviormetrics and Data Science [[electronic resource] ] : Essays in Honor of Akinori Okada / / edited by Tadashi Imaizumi, Atsuho Nakayama, Satoru Yokoyama
| Advanced Studies in Behaviormetrics and Data Science [[electronic resource] ] : Essays in Honor of Akinori Okada / / edited by Tadashi Imaizumi, Atsuho Nakayama, Satoru Yokoyama |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (XV, 472 p. 136 illus., 69 illus. in color.) |
| Disciplina | 658.8342 |
| Collana | Behaviormetrics: Quantitative Approaches to Human Behavior |
| Soggetto topico |
Statistics
Motivation research (Marketing) Mathematics Visualization Social sciences Psychometrics Statistics for Social Sciences, Humanities, Law Statistical Theory and Methods Consumer Behavior Methodology of the Social Sciences |
| ISBN | 981-15-2700-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Co-clustering for object by variable data matrices -- How to use the Hermitian Form Model for asymmetric MDS -- Asymmetric scaling models for square contingency tables: points, circles, arrows, and odds ratios -- Comparing partitions of the Petersen graph -- Minkowski distances and standardisation for clustering and classification on high dimensional data. . |
| Record Nr. | UNINA-9910484981703321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advanced studies in classification and data science / / Tadashi Imaizumi [and five others], editors
| Advanced studies in classification and data science / / Tadashi Imaizumi [and five others], editors |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Gateway East, Singapore : , : Springer, , [2020] |
| Descrizione fisica | 1 online resource (XI, 524 p. 121 illus., 64 illus. in color.) |
| Disciplina | 519.5 |
| Collana | Studies in classification, data analysis, and knowledge organization |
| Soggetto topico | Mathematical statistics |
| ISBN | 981-15-3311-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Multilevel model-based clustering: A new proposal of maximum-a-posteriori assignment -- Chapter 2. Multi-citeria classifications in regional development modelling -- Chapter 3. Non-parametric latent modeling and network clustering -- Chapter 4. Efficient, Geometrically-adaptive Techniques for Multiscale Gaussian-kernel SVM Classification -- Chapter 5. Random forests followed by computed ABC analysis as a feature selection method for machine-learning in biomedical data -- Chapter 6. Non-Hierarchical Clustering for Large Data without Recalculating Cluster Center -- Chapter 7. Supervised Nested Algorithm for Classification based on K-means -- Chapter 8. Using Classification of Regions Based on the Complexity of the Global Progress Indices for Supporting Development in Competitiveness -- Chapter 9. Estimation Methods Based on Weighting Clusters -- Chapter 10. Five Strategies for Accommodating Overdispersion in Simple Correspondence Analysis -- Chapter 11. From Joint Graphical Display to Bi-Modal Clustering: [2] Dual Space Versus Total Space -- Chapter 12. Linear Time Visualization and Search in Big Data using Pixellated Factor Space Mapping -- Chapter 13. From Joint Graphical Display to Bi-Modal Clustering: [1] A Giant Leap in Quantication Theory -- Chapter 14. External Logistic Biplots for Mixed Types of Data -- Chapter 15. Functional clustering approach for analysis of concentration -- Chapter 16. Generalized additive models for the detection of copy number variations (CNVs) using multi gene panel sequencing data -- Chapter 17. Variable selection for classification of multivariate functional data -- Chapter 18. Initial value selection for the alternating least squares algorithm -- Chapter 19. Inference for General MANOVA Based on ANOVA-Type Statistic -- Chapter 20. How To Cross the River? - New ‘Distance’Measures -- Chapter 21. New Statistical Matching Method Using Multinomial Logistic Regression Model -- Chapter 22. Constructing graphical models for multi-source data: Sparse Network And Component analysis -- Chapter 23. Understanding Malvestuto’s normalized mutual information -- Chapter 24. Understanding the Rand index -- Chapter 25. Layered Multivariate Regression with Its Applications -- Chapter 26. An exploratory study on the clumpiness measure of intertransaction times: how is it useful for customer relationship management? -- Chapter 27. Data Quality Management of Chain Stores based on Outlier Detection -- Chapter 28. Analysis of expenditure pattens of virtual marriage households consisting of working couples synthesized by statistical matching method q -- Chapter 29. The Effects of Natural Disasters on Household Income and Poverty in Rural Vietnam: An Analysis Using the Vietnam Household Living Standards Survey -- Chapter 30. Generalizability of relationship between number of tweets about and sales of new beverage products -- Chapter 31. Cluster Distance-Based Regression -- Chapter 32. Bayesian network analysis of fashion behaviour -- Chapter 33. Determining the Similarity Index in Electoral Behavior Analysis: An Issue Voting Behavioral:Mapping -- Chapter 34. Well-Being Measures -- Chapter 35. The Relationship between Household Assets and Choice to Work: Evidence from Japanese Official Microdata -- Chapter 36. Visualization and Spatial Statistical Analysis for Vietnam Household Living Standard Survey -- Chapter 37. Changes in the Gendered Division of Labor and Women’s Economic Contributions within Japanese Couples -- Chapter 38. Employment structures vs. educational capital in the European Union regions -- Chapter 39. The IPUMS Approach to Harmonizing the World’s Population Census Data -- Chapter 40. A Supervised Multiclass Classifieras an Autocoding System for the Family Income and Expenditure Survey -- . |
| Record Nr. | UNINA-9910484518303321 |
| Gateway East, Singapore : , : Springer, , [2020] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advanced studies in classification and data science / / Tadashi Imaizumi [and five others], editors
| Advanced studies in classification and data science / / Tadashi Imaizumi [and five others], editors |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Gateway East, Singapore : , : Springer, , [2020] |
| Descrizione fisica | 1 online resource (XI, 524 p. 121 illus., 64 illus. in color.) |
| Disciplina | 519.5 |
| Collana | Studies in classification, data analysis, and knowledge organization |
| Soggetto topico | Mathematical statistics |
| ISBN | 981-15-3311-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Multilevel model-based clustering: A new proposal of maximum-a-posteriori assignment -- Chapter 2. Multi-citeria classifications in regional development modelling -- Chapter 3. Non-parametric latent modeling and network clustering -- Chapter 4. Efficient, Geometrically-adaptive Techniques for Multiscale Gaussian-kernel SVM Classification -- Chapter 5. Random forests followed by computed ABC analysis as a feature selection method for machine-learning in biomedical data -- Chapter 6. Non-Hierarchical Clustering for Large Data without Recalculating Cluster Center -- Chapter 7. Supervised Nested Algorithm for Classification based on K-means -- Chapter 8. Using Classification of Regions Based on the Complexity of the Global Progress Indices for Supporting Development in Competitiveness -- Chapter 9. Estimation Methods Based on Weighting Clusters -- Chapter 10. Five Strategies for Accommodating Overdispersion in Simple Correspondence Analysis -- Chapter 11. From Joint Graphical Display to Bi-Modal Clustering: [2] Dual Space Versus Total Space -- Chapter 12. Linear Time Visualization and Search in Big Data using Pixellated Factor Space Mapping -- Chapter 13. From Joint Graphical Display to Bi-Modal Clustering: [1] A Giant Leap in Quantication Theory -- Chapter 14. External Logistic Biplots for Mixed Types of Data -- Chapter 15. Functional clustering approach for analysis of concentration -- Chapter 16. Generalized additive models for the detection of copy number variations (CNVs) using multi gene panel sequencing data -- Chapter 17. Variable selection for classification of multivariate functional data -- Chapter 18. Initial value selection for the alternating least squares algorithm -- Chapter 19. Inference for General MANOVA Based on ANOVA-Type Statistic -- Chapter 20. How To Cross the River? - New ‘Distance’Measures -- Chapter 21. New Statistical Matching Method Using Multinomial Logistic Regression Model -- Chapter 22. Constructing graphical models for multi-source data: Sparse Network And Component analysis -- Chapter 23. Understanding Malvestuto’s normalized mutual information -- Chapter 24. Understanding the Rand index -- Chapter 25. Layered Multivariate Regression with Its Applications -- Chapter 26. An exploratory study on the clumpiness measure of intertransaction times: how is it useful for customer relationship management? -- Chapter 27. Data Quality Management of Chain Stores based on Outlier Detection -- Chapter 28. Analysis of expenditure pattens of virtual marriage households consisting of working couples synthesized by statistical matching method q -- Chapter 29. The Effects of Natural Disasters on Household Income and Poverty in Rural Vietnam: An Analysis Using the Vietnam Household Living Standards Survey -- Chapter 30. Generalizability of relationship between number of tweets about and sales of new beverage products -- Chapter 31. Cluster Distance-Based Regression -- Chapter 32. Bayesian network analysis of fashion behaviour -- Chapter 33. Determining the Similarity Index in Electoral Behavior Analysis: An Issue Voting Behavioral:Mapping -- Chapter 34. Well-Being Measures -- Chapter 35. The Relationship between Household Assets and Choice to Work: Evidence from Japanese Official Microdata -- Chapter 36. Visualization and Spatial Statistical Analysis for Vietnam Household Living Standard Survey -- Chapter 37. Changes in the Gendered Division of Labor and Women’s Economic Contributions within Japanese Couples -- Chapter 38. Employment structures vs. educational capital in the European Union regions -- Chapter 39. The IPUMS Approach to Harmonizing the World’s Population Census Data -- Chapter 40. A Supervised Multiclass Classifieras an Autocoding System for the Family Income and Expenditure Survey -- . |
| Record Nr. | UNISA-996418251303316 |
| Gateway East, Singapore : , : Springer, , [2020] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||