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Between Data Science and Applied Data Analysis

Overview of attention for book
Cover of 'Between Data Science and Applied Data Analysis'

Table of Contents

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    Book Overview
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    Chapter 1 Robust Classification Through the Forward Search
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    Chapter 2 Fitting and Smoothing Properties of Length Constrained Smoothers Applied to Time Series
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    Chapter 3 Interaction Terms in Non-linear PLS via Additive Spline Transformation
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    Chapter 4 Discriminant Analysis With Categorical Variables: A Biplot Based Approach
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    Chapter 5 Efficient Density Clustering Using Basin Spanning Trees
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    Chapter 6 Some Issues on Clustering of Functional Data
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    Chapter 7 Scalable Clustering of High Dimensional Data
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    Chapter 8 Methods to Combine Classification Trees
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    Chapter 9 Core-Based Clustering Techniques
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    Chapter 10 Combining Regression Trees and Radial Basis Function Networks in Longitudinal Data Modelling
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    Chapter 11 Implementing a new Method for Discriminant Analysis When Group Covariance Matrices are Nearly Singular
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    Chapter 12 Two Approaches for Discriminant Partial Least Squares
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    Chapter 13 Improving the Classification Performance of a Discriminant Rule by Dealing With Data Cases Having a Substantial Influence on Variable Selection
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    Chapter 14 Classification and Clustering of Vocal Performances
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    Chapter 15 Cluster- and Discriminant Analysis With Both Metric and Categorial Data
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    Chapter 16 Multivariate Mixture Models Estimation: A Genetic Algorithm Approach
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    Chapter 17 Two-Way Clustering for Contingency Tables: Maximizing a Dependence Measure
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    Chapter 18 Localised Mixtures of Experts for Mixture of Regressions
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    Chapter 19 A Bayesian Approach for the Estimation of the Covariance Structure of Separable Spatio-Temporal Stochastic Processes
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    Chapter 20 An Algorithm for the HICLAS-R Model
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    Chapter 21 Some Applications of Time-Varying Coefficient Models to Count Data
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    Chapter 22 On Ziggurats and Dendrograms
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    Chapter 23 A Dimensionality Reduction Method Based on Simple Linear Regressions
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    Chapter 24 Evolutionary Strategies to Avoid Local Minima in Multidimensional Scaling
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    Chapter 25 Principal Component Analysis of Boolean Symbolic Objects
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    Chapter 26 Multivariate Analysis for Variables of Arbitrary Information Level
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    Chapter 27 How Wrong Models Become Useful — and Correct Models Become Dangerous
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    Chapter 28 Visualizing Symbolic Data by Closed Shapes
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    Chapter 29 LBGU-EM Algorithm for Mixture Density Estimation
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    Chapter 30 Change-Points in Bernoulli Trials With Dependence
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    Chapter 31 Two-Mode Clustering Methods: Compare and Contrast
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    Chapter 32 Sensitivity of Graphical Modeling Against Contamination
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    Chapter 33 New Graphical Symbolic Objects Representations in Parallel Coordinates
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    Chapter 34 A Hierarchical Classes Approach to Discriminant Analysis
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    Chapter 35 Prediction Optimal Data Analysis by Means of Stochastic Search
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    Chapter 36 System Error Variance Tuning in State-Space Models
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    Chapter 37 Corrado Gini and Multivariate Statistical Analysis: The (so far) Missing Link
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    Chapter 38 On Correspondence Analysis of Incomplete Orderings
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    Chapter 39 Some Statistical Issues in Microarray Data Analysis
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    Chapter 40 Background of the Variability in Past Human Populations: Selected Methodological Issues
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    Chapter 41 Spatial Prediction With Space-Time Models
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    Chapter 42 Neural Budget Networks of Sensorial Data
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    Chapter 43 Evolutionary Model Selection in Bayesian Neural Networks
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    Chapter 44 Extreme Datamining
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    Chapter 45 Information Filtering Based on Modal Symbolic Objects
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    Chapter 46 Analyzing Learner Behavior and Performance
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    Chapter 47 An Integration Strategy for Distributed Recommender Services in Legacy Library Systems
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    Chapter 48 Comparing Simple Association-Rules and Repeat-Buying Based Recommender Systems in a B2B Environment
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    Chapter 49 Students’ Preferences Related to Web Based E-Learning: Results of a Survey
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    Chapter 50 MURBANDY: The (so far) Missing Link: User-Friendly Retrieval and Visualization of Geographic Information
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    Chapter 51 ASCAID: Using an Asymmetric Correlation Measure for Automatic Interaction Detection
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    Chapter 52 Discriminative Clustering: Vector Quantization in Learning Metrics
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    Chapter 53 Neural Network Hybrid Learning: Genetic Algorithms & Levenberg-Marquardt
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    Chapter 54 Syntagmatic and Paradigmatic Associations in Information Retrieval
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    Chapter 55 Finding the Most Useful Clusters: Clustering and the Usefulness Metric
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    Chapter 56 Internet Thesaurus — Extracting Relevant Terms from WWW Pages using Weighted Threshold Function over a Cross-Reference Matrix
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    Chapter 57 Reflections on a Supervised Approach to Independent Component Analysis
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    Chapter 58 Simulated Annealing and Tabu Search for Optimization of Neural Networks
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    Chapter 59 Decentralizing Risk Management in the Case of Quadratic Hedging
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    Chapter 60 Multimedia Stimulus Presentation Methods for Conjoint Studies in Marketing Research
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    Chapter 61 Forecasting the Customer Development of a Publishing Company with Decision Trees
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    Chapter 62 Estimation of Default Probabilities in a Single-Factor Model
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    Chapter 63 Simultaneous Confidence Intervals for Default Probabilities
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    Chapter 64 Model-Based Clustering With Hidden Markov Models and its Application to Financial Time-Series Data
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    Chapter 65 Classification of Multivariate Data With Missing Values Using Expected Discriminant Scores
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    Chapter 66 Assessment of the Polish Manufacturing Sector Attractiveness: An End-User Approach
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    Chapter 67 Developing a Layout of a Supermarket Through Asymmetric Multidimensional Scaling and Cluster Analysis of Purchase Data
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    Chapter 68 Market Segmentation Method From the Bayesian Viewpoint
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    Chapter 69 Support Vector Machines for Credit Scoring: Comparing to and Combining With Some Traditional Classification Methods
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    Chapter 70 Classification of Amino-Acid Sequences Using State-Space Models
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    Chapter 71 Quantitative Study of Images in Archaeology: I. Textual Coding
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    Chapter 72 Quantitative Study of Images in Archaeology: II. Symbolic Coding
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    Chapter 73 Power Functions in Multiple Sampling Plans Using DNA Computation
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    Chapter 74 Methodological Issues in the Baffling Relationship Between Hepatitis C Virus and Non Hodgkin’s Lymphomas
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    Chapter 75 Class Discovery in Gene Expression Data: Characterizing Splits by Support Vector Machines
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    Chapter 76 Efficient Clustering Methods for Tumor Classification With Microarrays
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    Chapter 77 A Method to Classify Microarray Data
Overall attention for this book and its chapters
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Title
Between Data Science and Applied Data Analysis
Published by
Springer Berlin Heidelberg, December 2012
DOI 10.1007/978-3-642-18991-3
ISBNs
978-3-54-040354-8, 978-3-64-218991-3
Editors

Schader, Martin, Gaul, Wolfgang, Vichi, Maurizio

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 200%
Student > Doctoral Student 1 100%
Student > Master 1 100%
Readers by discipline Count As %
Computer Science 2 200%
Agricultural and Biological Sciences 1 100%
Engineering 1 100%

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