Recent Developments in Clustering and Data Analysis
Développements Récents en Classification Automatique et Analyse des Données: Proceedings of the Japanese-French Scientific Seminar March 24–26, 1987
- 1st Edition - September 23, 2014
- Editors: Chikio Hayashi, Michel Jambu, Edwin Diday
- Language: English
- Paperback ISBN:9 7 8 - 1 - 4 8 3 2 - 3 8 1 5 - 9
- eBook ISBN:9 7 8 - 1 - 4 8 3 2 - 6 3 0 9 - 0
Recent Developments in Clustering and Data Analysis presents the results of clustering and multidimensional data analysis research conducted primarily in Japan and France. This… Read more
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Recent Developments in Clustering and Data Analysis presents the results of clustering and multidimensional data analysis research conducted primarily in Japan and France. This book focuses on the significance of the data itself and on the informatics of the data. Organized into four sections encompassing 35 chapters, this book begins with an overview of the quantification of qualitative data as a method of analyzing statistically multidimensional data. This text then examines the rules of interpretation of correspondence cluster analysis by selecting classes and explaining variables involved in the algorithm of hierarchical classification. Other chapters consider the bootstrap and cross-validation methods, which are applied to the logistic ad nonparametric regression analyses of ordered categorical responses. The final chapter deals with a simpler treatment to classify the sleep state. This book is a valuable resource for researchers and workers in the fields from the behavioral sciences, biological sciences, medicine, and industrial sciences.
Contributors
Preface
Section 1 Data Analysis Techniques and Related Topics with Statistical Software
New Developments in Multidimensional Data Analysis
Interpretation of Some Data Analysis Methods
A General Euclidean Approach for Measuring and Describing Associations Between Several Sets of Variables
Data-Adaptive Methods in Multivariate Analysis
Specific Design of a Software for Multivariate Descriptive Statistical Analysis: The Case of SPAD.N
A Test of Goodness of Fit Based on Graphical Method
Graphical Analysis of Ranks
A Unified Study of Multivariate Data Analysis Methods by Nonlinear Formulations and Underlying Probabilistic Structures
Optimum Classification Boundaries Based on a Concomitant Variable in Sample Survey: Some Application to the Current Statistics of Commerce
On the Identification Problem of Age-Period-Cohort Analysis
Section 2 Automatic Classification and Related Techniques
Some Recent Advances in Clustering
Simultaneous Clustering of Cases amd Variances
Techniques of Approximation for Building Two Tree Structures
A Hierarchical Clustering Method for Dissimilarity Matrices with Individual Differences
Applications of Multivariate and Cladistic Data Analyses for the Classification of Dermapterous Insects
Comparing Relational Variables According to Likelihood of the Links Classification Method
Role of Computer Graphics in Interpretation of Clustering Results
Classification of Fruit and Vegetable Varieties by Chemical Analysis of Fragrance Substances
Section 3 Scaling Method and Correspondence Analysis from the Viewpoint of Practical Approach
Assessing the Number of Axes that Should Be Considered in Correspondence Analysis
Singular Value Decomposition of Multiarray Data and Its Applications
Partial Correspondence Analysis and Its Properties
Correlation Analysis of N-Way Qualitative Data and Its Applications
Outliers and Influential Observations in Quantification Theory
Conversational Data Analysis System: Selection of Items and Pooling of Categories
Analysis and Comparison of Different Tables
Use of Tabulated Data in Data Analysis
Section 4 Applications: Extraction and Interpretation of Information in Multidimensional Data
Mutivariate Descriptive Techniques Applied to the Processing of Longitudinal Sample Survey Data
Multidimensional Analysis of Opinion Survey Data
Data Analytic Approaches to Human Behavioral Relationships in Survey of Accidents
About the Numerical and Statistical Stability of Forecasting Algorithms
The Method of Pattern Classification and Its Application to Prognosis of Disease
A Non Parametric Discriminant Analysis Based on the Construction of a Binary Decision Tree
Experimental Comparison Between the Optimal Discriminate Plane Based on Samples and General Discriminant Analysis
A Method of Discrimination for Electrical Biosignal
Classification of Behavioral States of the Mouse
- Edition: 1
- Published: September 23, 2014
- Language: English
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