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New Approaches in Classification and Data Analysis

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Cover of 'New Approaches in Classification and Data Analysis'

Table of Contents

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    Book Overview
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    Chapter 1 Classification and Clustering: Problems for the Future
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    Chapter 2 From classifications to cognitive categorization: the example of the road lexicon
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    Chapter 3 A review of graphical methods in Japan — from histogram to dynamic display —
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    Chapter 4 New Data and New Tools: A Hypermedia Environment for Navigating Statistical Knowledge in Data Science
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    Chapter 5 On the logical necessity and priority of a monothetic conception of class, and on the consequent inadequacy of polythetic accounts of category and categorization
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    Chapter 6 Research and Applications of Quantification Methods in East Asian Countries
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    Chapter 7 Algorithms for a geometrical P.C.A. with the L 1 -norm
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    Chapter 8 Comparison of hierarchical classifications
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    Chapter 9 On quadripolar Robinson dissimilarity matrices
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    Chapter 10 An Ordered Set Approach to Neutral Consensus Functions
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    Chapter 11 From Apresjan Hierarchies and Bandelt-Dress Weak hierarchies to Quasi-hierarchies
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    Chapter 12 Spanning trees and average linkage clustering
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    Chapter 13 Adjustments of tree metrics based on minimum spanning trees
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    Chapter 14 The complexity of the median procedure for binary trees
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    Chapter 15 A multivariate analysis of a series of variety trials with special reference to classification of varieties
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    Chapter 16 Quality control of mixture. Application: The grass
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    Chapter 17 Mixture Analysis with Noisy Data
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    Chapter 18 Locally optimal tests on spatial clustering
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    Chapter 19 Choosing the Number of Clusters, Subset Selection of Variables, and Outlier Detection in the Standard Mixture-Model Cluster Analysis
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    Chapter 20 An examination of procedures for determining the number of clusters in a data set
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    Chapter 21 The gap test: an optimal method for determining the number of natural classes in cluster analysis
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    Chapter 22 Mode detection and valley seeking by binary morphological analysis of connectivity for pattern classification
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    Chapter 23 Interactive Class Classification Using Types
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    Chapter 24 K-means clustering in a low-dimensional Euclidean space
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    Chapter 25 Complexity relaxation of dynamic programming for cluster analysis
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    Chapter 26 Partitioning Problems in Cluster Analysis: A Review of Mathematical Programming Approaches
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    Chapter 27 Clusters and factors: neural algorithms for a novel representation of huge and highly multidimensional data sets
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    Chapter 28 Graphs and structural similarities
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    Chapter 29 A generalisation of the diameter criterion for clustering
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    Chapter 30 Percolation and multimodal data structuring
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    Chapter 31 Classification and Discrimination Techniques Applied to the Early Detection of Business Failure
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    Chapter 32 Recursive Partition and Symbolic Data Analysis
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    Chapter 33 Interpretation Tools For Generalized Discriminant Analysis
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    Chapter 34 Inference about rejected cases in discriminant analysis
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    Chapter 35 Structure Learning of Bayesian Networks by Genetic Algorithms
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    Chapter 36 On the representation of observational data used for classification and identification of natural objects
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    Chapter 37 Alternative strategies and CATANOVA testing in two-stage binary segmentation
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    Chapter 38 Alignment, Comparison and Consensus of Molecular Sequences
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    Chapter 39 An Empirical Evaluation of Consensus Rules for Molecular Sequences
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    Chapter 40 A Probabilistic Approach To Identifying Consensus In Molecular Sequences
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    Chapter 41 Applications of Distance Geometry to Molecular Conformation
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    Chapter 42 Classification of aligned biological sequences
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    Chapter 43 Use of Pyramids in Symbolic Data Analysis
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    Chapter 44 Proximity Coefficients between Boolean symbolic objects
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    Chapter 45 Conceptual Clustering in Structured Domains: A Theory Guided Approach
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    Chapter 46 Automatic Aid to Symbolic Cluster Interpretation
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    Chapter 47 Symbolic Clustering Algorithms using Similarity and Dissimilarity Measures
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    Chapter 48 Feature Selection for Symbolic Data Classification
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    Chapter 49 Towards extraction method of knowledge founded by symbolic objects
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    Chapter 50 One Method of Classification based on an Analysis of the Structural Relationship between Independent Variables
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    Chapter 51 The Integration of Neural Networks with Symbolic Knowledge Processing
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    Chapter 52 Ordering of Fuzzy k -Partitions
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    Chapter 53 On the Extension of Probability Theory and Statistics to the Handling of Fuzzy Data
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    Chapter 54 Fuzzy Regression
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    Chapter 55 Clustering and Aggregation of Fuzzy Preference Data: Agreement vs. Information
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    Chapter 56 Rough Classification with Valued Closeness Relation
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    Chapter 57 Representing proximities by network models
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    Chapter 58 An Eigenvector Algorithm to Fit l p -Distance Matrices
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    Chapter 59 A non linear approach to Non Symmetrical Data Analysis
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    Chapter 60 An Algorithmic Approach to Bilinear Models for Two-Way Contingency Tables
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    Chapter 61 New Approaches Based on Rankings in Sensory Evaluation
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    Chapter 62 Estimating failure times distributions from censored systems arranged in series
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    Chapter 63 Calibration Used as a Nonresponse Adjustment
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    Chapter 64 Least Squares Smoothers and Additive Decomposition
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    Chapter 65 High Dimensional Representations and Information Retrieval
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    Chapter 66 Experiments of Textual Data Analysis at Electricité de France
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    Chapter 67 Conception of a Data Supervisor in the Prospect of Piloting Management Quality of Service and Marketing
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    Chapter 68 Discriminant Analysis Using Textual Data
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    Chapter 69 Recent Developments in Case Based Reasoning: Improvements of Similarity Measures
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    Chapter 70 Contiguity in discriminant factorial analysis for image clustering
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    Chapter 71 Exploratory and Confirmatory Discrete Multivariate Analysis in a Probabilistic Approach for Studying the Regional Distribution of Aids in Angola
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    Chapter 72 Factor Analysis of Medical Image Sequences (FAMIS): Fundamental principles and applications
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    Chapter 73 Multifractal Segmentation of Medical Images
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    Chapter 74 The Human Organism — a Place to Thrive for the Immuno-Deficiency Virus
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    Chapter 75 Comparability and usefulness of newer and classical data analysis techniques. Application in medical domain classification
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    Chapter 76 The Classification of IRAS Point Sources
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    Chapter 77 Astronomical classification of the Hipparcos input catalogue
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    Chapter 78 Group identification and individual assignation of stars from kinematical and luminosity parameters
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    Chapter 79 Specific numerical and symbolic analysis of chronological series in view to classification of long period variable stars
Overall attention for this book and its chapters
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Title
New Approaches in Classification and Data Analysis
Published by
Springer Berlin Heidelberg, January 1994
DOI 10.1007/978-3-642-51175-2
ISBNs
978-3-54-058425-4, 978-3-64-251175-2
Editors

Diday, Edwin, Lechevallier, Yves, Schader, Martin, Bertrand, Patrice, Burtschy, Bernard

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

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The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 13%
Unknown 7 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 38%
Researcher 2 25%
Lecturer > Senior Lecturer 1 13%
Student > Master 1 13%
Unknown 1 13%
Readers by discipline Count As %
Mathematics 1 13%
Agricultural and Biological Sciences 1 13%
Computer Science 1 13%
Physics and Astronomy 1 13%
Decision Sciences 1 13%
Other 2 25%
Unknown 1 13%