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Data Analysis, Classification, and Related Methods

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Table of Contents

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    Book Overview
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    Chapter 1 Classifier Probabilities
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    Chapter 2 Cluster Analysis Based on Data Depth
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    Chapter 3 An Autonomous Clustering Technique
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    Chapter 4 Unsupervised Non-hierarchical Entropy-based Clustering
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    Chapter 5 Improving the Additive Tree Representation of a Dissimilarity Matrix Using Reticulations
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    Chapter 6 Double Versus Optimal Grade Clusterings
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    Chapter 7 The Effects of Initial Values and the Covariance Structure on the Recovery of some Clustering Methods
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    Chapter 8 What Clusters Are Generated by Normal Mixtures?
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    Chapter 9 A Bootstrap Procedure for Mixture Models
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    Chapter 10 A New Criterion for Obtaining a Fuzzy Partition from a Hybrid Fuzzy/Hierarchical Clustering Method
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    Chapter 11 Application of Fuzzy Mathematical Morphology for Unsupervised Color Pixels Classification
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    Chapter 12 A Hyperbolic Fuzzt k -Means Clustering and Algorithm for Neural Networks
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    Chapter 13 A Toolkit for Development of the Domain-Oriented Dictionaries for Structuring Document Flows
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    Chapter 14 Classification of Single Malt Whiskies
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    Chapter 15 Robust Approach in Hierarchical Clustering: Application to the Sectorisation of an Oil Field
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    Chapter 16 A Minimax Solution for Sequential Classification Problems
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    Chapter 17 Comparison of Ultrametrics Obtained With Real Data, Using the P L and VAL Aw Coefficients
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    Chapter 18 Numerical Comparisons of two Spectral Decompositions for Vertex Clustering
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    Chapter 19 Measures to Evaluate Rankings of Classification Algorithms
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    Chapter 20 A General Approach to Test the Pertinence of a Consensus Classification
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    Chapter 21 On a Class of Aggregation-invariant Dissimilarities Obeying the Weak Huygens’ Principle
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    Chapter 22 A Short Optimal Way for Constructing Quasi-ultrametrics From Some Particular Dissimilarities
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    Chapter 23 Estimating Missing Values in a Tree Distance
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    Chapter 24 Estimating Trees From Incomplete Distance Matrices: A Comparison of Two Methods
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    Chapter 25 Zero Replacement in Compositional Data Sets
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    Chapter 26 EM Algorithm for Partially Known Labels
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    Chapter 27 Detection of Company Failure and Global Risk Forecasting
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    Chapter 28 Discriminant Analysis by Hierarchical Coupling in EDDA Context
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    Chapter 29 Discrete Discriminant Analysis: The Performance of Combining Models by a Hierarchical Coupling Approach
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    Chapter 30 Discrimination Based on the Atypicity Index versus Density Function Ratio
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    Chapter 31 A Third Stage in Regression Tree Growing: Searching for Statistical Reliability
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    Chapter 32 A New Sampling Strategy for Building Decision Trees from Large Databases
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    Chapter 33 Generalized Additive Multi-Model for Classification and Prediction
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    Chapter 34 Radial Basis Function Networks and Decision Trees in the Determination of a Classifier
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    Chapter 35 Clustered Multiple Regression
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    Chapter 36 Constructing Artificial Neural Networks for Censored Survival Data from Statistical Models
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    Chapter 37 Visualisation and Classification with Artificial Life
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    Chapter 38 Exploring the Periphery of Data Scatters: Are There Outliers?
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    Chapter 39 Discriminant Analysis Tools for Non Convex Pattern Recognition
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    Chapter 40 A Markovian Approach to Unsupervised Multidimensional Pattern Classification
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    Chapter 41 An Algorithm with Projection Pursuit for Sliced Inverse Regression Model
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    Chapter 42 Testing Constraints and Misspecification in VAR-ARCH Models
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    Chapter 43 Goodness of Fit Measure Based on Sample Isotone Regression of Mokken Double Monotonicity Model
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    Chapter 44 Fuzzy Time Arrays and Dissimilarity Measures For Fuzzy Time Trajectories
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    Chapter 45 Three-Way Partial Correlation Measures
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    Chapter 46 Statistical Models for Social Networks
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    Chapter 47 Application of Simulated Annealing in some Multidimensional Scaling Problems
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    Chapter 48 Data Analysis Based on Minimal Closed Subsets
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    Chapter 49 A Robust Method for Multivariate Regression
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    Chapter 50 Robust Methods for Complex Data Structures
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    Chapter 51 Robust Methods for Canonical Correlation Analysis
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    Chapter 52 From Data Analysis to Data Science
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    Chapter 53 Evaluation of Data Quality and Data Analysis
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    Chapter 54 Collapsibility and Collapsing Multidimensional Contingency Tables—Perspectives and Implications
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    Chapter 55 Data Collected on the Web
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    Chapter 56 Some Experimental Surveys on the WWW Environments in Japan
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    Chapter 57 Bootstrap Goodness-of-fit Tests for Complex Survey Samples
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    Chapter 58 Regression Analysis for Interval-Valued Data
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    Chapter 59 Symbolic Approach to Classify Large Data Sets
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    Chapter 60 Factorial Methods with Cohesion Constraints on Symbolic Objects
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    Chapter 61 A Dynamical Clustering Algorithm for Multi-nominal Data
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    Chapter 62 DB2SO: A Software for Building Symbolic Objects from Databases
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    Chapter 63 Symbolic Data Analysis and the SODAS Software in Official Statistics
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    Chapter 64 Strata Decision Tree SDA Software
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    Chapter 65 Marking and Generalization by Symbolic Objects in the Symbolic Official Data Analysis Software
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Title
Data Analysis, Classification, and Related Methods
Published by
Springer Berlin Heidelberg, December 2012
DOI 10.1007/978-3-642-59789-3
ISBNs
978-3-54-067521-1, 978-3-64-259789-3
Editors

Kiers, Henk A. L., Schader, Martin, Groenen, Patrick J. F., Rasson, Jean-Paul

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 1 8%
Unknown 12 92%
Readers by discipline Count As %
Engineering 1 8%
Unknown 12 92%