Okada / Imaizumi / Bock Cooperation in Classification and Data Analysis

Proceedings of Two German-Japanese Workshops
1. Auflage 2009
ISBN: 978-3-642-00668-5
Verlag: Springer
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 208 Seiten

Autoren/Hrsg.

Okada, Akinori

Imaizumi, Tadashi

Bock, Hans-Hermann

Inhaltsverzeichnis

1;Preface;5
2;Contents;7
3;Contributors;9
4;Classification and Visualization;12
4.1;Analyzing Symbolic Data: Problems, Methods, and Perspectives;13
4.1.1;1 Introduction;13
4.1.2;2 Visualization Tools: Zoom Stars and Principal Component Analysis;14
4.1.3;3 Dissimilarity Between Data Rectangles;15
4.1.4;4 Average Intervals and Class Prototypes: Centrocubes;16
4.1.5;5 Partitioning Clustering Methods;18
4.1.6;6 A Parametric Probabilistic Approach for Clustering Interval Data;19
4.1.7;7 FinalRemarks;21
4.1.8;References;21
4.2;Constraining Shape and Size in Clustering;23
4.2.1;1 Introduction;23
4.2.2;2 Mixture Models and the EM Algorithm;24
4.2.3;3 Fuzzy Clustering;25
4.2.4;4 Constraining Cluster Parameters;28
4.2.5;5 Experiments;32
4.2.6;6 Conclusions;34
4.2.7;References;35
4.3;Dissolution and Isolation Robustness of Fixed Point Clusters;36
4.3.1;1 Introduction;36
4.3.2;2 Robustness Concepts;37
4.3.3;3 Fixed Point Clusters;39
4.3.4;4 Proofs;45
4.3.5;References;47
4.4;ADCLUS: A Data Model for the Comparison of Two- Mode Clustering Methods by Monte Carlo Simulation;49
4.4.1;1 Introduction;49
4.4.2;2 The ADCLUS Model as a General Model for Generating Clustered Data;50
4.4.3;3 An Exemplifying Simulation Study;54
4.4.4;4 Conclusions;57
4.4.5;References;58
4.5;Density-Based Multidimensional Scaling;60
4.5.1;1 Introduction;60
4.5.2;2 Sammon's Mapping;61
4.5.3;3 Density-Based Mappings;62
4.5.4;4 Results;65
4.5.5;5 Conclusions;67
4.5.6;References;67
4.6;Classification of Binary Data Using a Spherical Distribution;68
4.6.1;1 Introduction;68
4.6.2;2 Transformation Binary Data into Directional Data;69
4.6.3;3 Distribution on a Hypersphere;71
4.6.4;4 Discriminant Function;73
4.6.5;5 Numerical Experiments;74
4.6.6;6 Concluding Remarks;75
4.6.7;References;76
4.7;Fuzzy Clustering Based Regression with Attribute Weights;77
4.7.1;1 Introduction;77
4.7.2;2 Fuzzy Clustering Considering Attributes;78
4.7.3;3 Fuzzy Cluster Loading Model;79
4.7.4;4 A Weighted Regression Analysis Using Fuzzy Clustering;81
4.7.5;5 Attribute Based Fuzzy Cluster Loading Model and a Fuzzy Weighted Regression Analysis;81
4.7.6;6 Numerical Example;82
4.7.7;7 Conclusion;85
4.7.8;References;85
4.8;Polynomial Regression on a Dependent Variable with Immeasurable Observations;87
4.8.1;1 Introduction;87
4.8.2;2 Preliminaries;88
4.8.3;3 Likelihood Functions;89
4.8.4;4 Simulation Studies;90
4.8.5;5 Conclusion;93
4.8.6;References;94
5;Methods in Fields;95
5.1;Feedback Options for a Personal News Recommendation Tool;96
5.1.1;1 Introduction;96
5.1.2;2 Interest Profiles;97
5.1.3;3 Feedback Options;98
5.1.4;4 Web Page Classification;99
5.1.5;5 Evaluation Method;100
5.1.6;6 Empirical Results;101
5.1.7;7 Conclusions;102
5.1.8;References;103
5.2;Classification in Marketing Science;104
5.2.1;1 Introduction;104
5.2.2;2 Data Description and Preprocessing;105
5.2.3;3 Growing Bisecting k-Means: A Methodological Outline;106
5.2.4;4 Application to Marketing Text Corpus;108
5.2.5;5 Conclusions;110
5.2.6;References;110
5.3;Deriving a Statistical Model for the Prediction of Spiralling in BTA Deep- Hole- Drilling from a Physical Model;112
5.3.1;1 Introduction;112
5.3.2;2 Physical Model;114
5.3.3;3 Statistical Model;115
5.3.4;4 Summary and Outlook;118
5.3.5;References;119
5.4;Analyzing Protein-Protein Interaction with Variant Analysis;120
5.4.1;1 Introduction;120
5.4.2;2 Parameter Estimation Under Ambiguity and Contamination;121
5.4.3;3 Study of a Protein-Protein Interaction;124
5.4.4;References;127
5.5;Estimation for the Parameters in Geostatistics;128
5.5.1;1 Introduction;128
5.5.2;2 Using Geostatistics for Prediction;129
5.5.3;3 Non-negative Least Squares Method for Nonlinear Model ( NNLS);132
5.5.4;4 Numerical Example;134
5.5.5;5 Conclusion and Future Research;135
5.6;Identifying Patients at Risk: Mining Dialysis Treatment Data;136
5.6.1;1 Introduction;136
5.6.2;2 Background and RelatedWork;137
5.6.3;3 The Data-set;138
5.6.4;4 Standard Model;139
5.6.5;5 Temporal Model;140
5.6.6;6 MixedModel;143
5.6.7;7 Summary and Outlook;144
5.6.8;References;144
5.7;Sequential Multiple Comparison Procedure for Finding a Changing Point in Dose Finding Test;146
5.7.1;1 Introduction;146
5.7.2;2 Sequential Multiple Comparison Procedure;147
5.7.3;3 Critical Value;148
5.7.4;4 Power of Test and Necessary Sample Size;149
5.7.5;5 A Simulation Study;150
5.7.6;6 A Case Study;151
5.7.7;7 Conclusions;152
5.7.8;References;154
5.8;Semi-supervised Clustering of Yeast Gene Expression Data;155
5.8.1;1 Introduction;155
5.8.2;2 Methods;156
5.8.3;3 Results;159
5.8.4;4 Conclusion;161
5.8.5;References;162
5.9;Event Detection in Environmental Scanning: News from a Hospitality Industry Newsletter;164
5.9.1;1 Introduction;164
5.9.2;2 Data Description and Preprocessing;165
5.9.3;3 Methodology;166
5.9.4;4 Discussion and Conclusions;171
5.9.5;References;171
6;Applications in Clustering and Visualization;172
6.1;External Asymmetric Multidimensional Scaling Study of Regional Closeness in Marriage Among Japanese Prefectures;173
6.1.1;1 Introduction;173
6.1.2;2 TheData;174
6.1.3;3 TheMethod;174
6.1.4;4 The Analysis;175
6.1.5;5 Results;175
6.1.6;6 Discussion;177
6.1.7;References;180
6.2;Socioeconomic and Age Differences in Women's Cultural Consumption: Multidimensional Preference Analysis;181
6.2.1;1 Social Patterning of Cultural Consumption;181
6.2.2;2 Data;182
6.2.3;3 Results;183
6.2.4;4 Discussion and Conclusion;188
6.2.5;References;188
6.3;Analysis of Purchase Intentions at a Department Store by Three- Way Distance Model;190
6.3.1;1 Introduction;190
6.3.2;2 Data;191
6.3.3;3 Analysis;192
6.3.4;4 Results;193
6.3.5;5 Discussion;195
6.3.6;References;197
6.4;Facet Analysis of the AsiaBarometer Survey: Well- being, Trust and Political Attitudes;198
6.4.1;1 Introduction;198
6.4.2;2 Results of Data Analysis;199
6.4.3;3 Conclusion;204
6.4.4;References;205
6.5;Author Index;206
6.6;Subject Index;207