Selected Contributions in Data Analysis and Classification
By inviting me to write a preface, the organizers of the event in honour of Edwin Diday, have expressed their a?ection and I appreciate this very much. This gives me an opportunity to express my friendship and admiration for Edwin Diday, and I wrote this foreword with pleasure. My ?rst few meetings...
Na minha lista:
| Autor principal: | |
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| Outros Autores: | , , , |
| Formato: | Livre numérique |
| Idioma: | Anglais |
| Publicado em: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Edição: | 1st ed. 2007. |
| Colecção: | Studies in Classification, Data Analysis, and Knowledge Organization
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| Assuntos: | |
| Acesso em linha: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
L'impression du document génère 618 p. Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Variante du titre: | Mélanges :, Diday |
| Edition sous un autre format: | • Selected Contributions in Data Analysis and Classification, Texte imprimé, 9783540840848 • Selected contributions in data analysis and classification, Paula Brito, Patrice Bertrand, Guy Cucumel... [et autres] (Eds), 2007, Berlin, Springer, 1 volume (xiii-634 pages), Studies in classification, data analysis, and knowledge organization, 978-3-540-73558-8 |
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| 084 | |a 68-06. 2010 | ||
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| 100 | 1 | |a Brito, Paula. | |
| 240 | 1 | 0 | |a Mélanges : |b Diday |
| 245 | 1 | 0 | |a Selected Contributions in Data Analysis and Classification |c Paula Brito, Patrice Bertrand, Guy Cucumel... ... [et autres] (Eds) ; With a Foreword by Yves Escoufier. |
| 250 | |a 1st ed. 2007. | ||
| 260 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 490 | 0 | |a Studies in Classification, Data Analysis, and Knowledge Organization |x 2198-3321 | |
| 500 | |a L'impression du document génère 618 p. | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 504 | |a Bibliogarphies en fin de contributuions. Index | ||
| 505 | 1 | |a Analysis of Symbolic Data Dependencies and Variation Components of Symbolic Interval-Valued Data On the Analysis of Symbolic Data Symbolic Analysis to Learn Evolving CyberTraffic A Clustering Algorithm for Symbolic Interval Data Based on a Single Adaptive Hausdorff Distance An Agglomerative Hierarchical Clustering Algorithm for Improving Symbolic Object Retrieval 3WaySym-Scal: Three-Way Symbolic Multidimensional Scaling Clustering and Validation of Interval Data Building Symbolic Objects from Data Streams Feature Clustering Method to Detect Monotonic Chain Structures in Symbolic Data Symbolic Markov Chains Quality Issues in Symbolic Data Analysis Dynamic Clustering of Histogram Data: Using the Right Metric Clustering Methods Beyond the Pyramids: Rigid Clustering Systems Indirect Blockmodeling of 3-Way Networks Clustering Methods: A History of k-Means Algorithms Overlapping Clustering in a Graph Using k-Means and Application to Protein Interactions Networks Species Clustering via Classical and Interval Data Representation Looking for High Density Zones in a Graph Block Bernoulli Parsimonious Clustering Models Cluster Analysis Based on Posets Hybrid k-Means: Combining Regression-Wise and Centroid-Based Criteria for QSAR Partitioning by Particle Swarm Optimization Conceptual Analysis of Data Concepts of a Discrete Random Variable Mining Description Logics Concepts with Relational Concept Analysis Representation of Concept Description by Multivalued Taxonomic Preordonance Variables Recent Advances in Conceptual Clustering: CLUSTER3 Symbolic Dynamics in Text: Application to Automated Construction of Concept Hierarchies Consensus Methods Average Consensus and Infinite Norm Consensus : Two Methods for Ultrametric Trees Consensus from Frequent Groupings Consensus of Star Tree Hypergraphs Data Analysis, Data Mining, and KDD Knowledge Management in Environmental Sciences with : Application to Systematics of Corals of the Mascarene Archipelago Unsupervised Learning Informational Limit in Case of Sparsely Described Examples Data Analysis and Operations Research Reduction of Redundant Rules in Statistical Implicative Analysis Mining Personal Banking Data to Detect Fraud Finding Rules in Data Mining Biological Data Using Pyramids Association Rules for Categorical and Tree Data Induction Graphs for Data Mining Dissimilarities: Structures and Indices Clustering of Molecules: Influence of the Similarity Measures Group Average Representations in Euclidean Distance Cones On Lower-Maximal Paired-Ultrametrics A Note on Three-Way Dissimilarities and Their Relationship with Two-Way Dissimilarities One-to-One Correspondence Between Indexed Cluster Structures and Weakly Indexed Closed Cluster Structures Adaptive Dissimilarity Index for Gene Expression Profiles Classification | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a By inviting me to write a preface, the organizers of the event in honour of Edwin Diday, have expressed their a?ection and I appreciate this very much. This gives me an opportunity to express my friendship and admiration for Edwin Diday, and I wrote this foreword with pleasure. My ?rst few meetings withEdwinDidaydatebackto1965through1975,daysofthedevelopmentof French statistics. This was a period when access to computers revolutionized the practice of statistics. This does not refer to individual computers or to terminals that have access to powerful networks. This was the era of the ?rst university calculation centres that one accessed over a counter. One would deposit cards on which program and data were punched in and come back a few hours or days later for the results. Like all those who used linear data analysis, the computer enabled me to calculate for each data set the value of mathematical objects (eigenvalues and eigenvectors for example) whose optimality properties had been demonstrated by mathematicians. It was - ready a big step to be able to do this in concrete experimental situations. With Dynamic Clustering Algorithm, Edwin Diday allowed us to discover that computers could be more than just a way of giving numerical values to known mathematical objects. Besides the e?ciency of the solutions he built, he led us to integrate the access to computers di?erently in the research and practice of data analysis | ||
| 650 | |a Analyse multivariée | ||
| 650 | |a Analyse des données | ||
| 650 | |a Analyse des données symboliques | ||
| 650 | |a Classification automatique | ||
| 700 | 1 | |a Bertrand, Patrice, |d 19..- |4 pbd | |
| 700 | 1 | |a Cucumel, Guy. |4 pbd | |
| 700 | 1 | |a De Carvalho, Francisco. |4 pbd | |
| 700 | 1 | |a Brito, Paula. |4 edt | |
| 700 | 1 | |a Escoufier, Yves, |d 1939-...., |c mathématicien. |4 aui | |
| 776 | 0 | |t Selected Contributions in Data Analysis and Classification |b Texte imprimé |z 9783540840848 | |
| 776 | 0 | |0 117447188 |t Selected contributions in data analysis and classification |f Paula Brito, Patrice Bertrand, Guy Cucumel... [et autres] (Eds) |d 2007 |c Berlin |n Springer |p 1 volume (xiii-634 pages) |s Studies in classification, data analysis, and knowledge organization |z 978-3-540-73558-8 | |
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| 997 | |0 939790 |1 Livre numérique |a Ressource numérique |b INSA |b ENSA |c 0/Bibliothèque numérique/ |c 1/Bibliothèque numérique/Autre ressource numérique/ | ||