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Data Analysis, Machine Learning and Knowledge Discovery

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Table of Contents

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    Book Overview
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    Chapter 1 On Limiting Donor Usage for Imputation of Missing Data via Hot Deck Methods
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    Chapter 2 The Most Dangerous Districts of Dortmund
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    Chapter 3 Benchmarking Classification Algorithms on High-Performance Computing Clusters
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    Chapter 4 Visual Models for Categorical Data in Economic Research
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    Chapter 5 How Many Bee Species? A Case Study in Determining the Number of Clusters
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    Chapter 6 Two-Step Linear Discriminant Analysis for Classification of EEG Data
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    Chapter 7 Predictive Validity of Tracking Decisions: Application of a New Validation Criterion
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    Chapter 8 DDα-Classification of Asymmetric and Fat-Tailed Data
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    Chapter 9 The Alpha-Procedure: A Nonparametric Invariant Method for Automatic Classification of Multi-Dimensional Objects
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    Chapter 10 Support Vector Machines on Large Data Sets: Simple Parallel Approaches
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    Chapter 11 Soft Bootstrapping in Cluster Analysis and Its Comparison with Other Resampling Methods
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    Chapter 12 Dual Scaling Classification and Its Application in Archaeometry
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    Chapter 13 Gamma-Hadron-Separation in the MAGIC Experiment
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    Chapter 14 Implementing Inductive Concept Learning For Cooperative Query Answering
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    Chapter 15 Clustering Large Datasets Using Data Stream Clustering Techniques
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    Chapter 16 Feedback Prediction for Blogs
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    Chapter 17 Spectral Clustering: Interpretation and Gaussian Parameter
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    Chapter 18 On the Problem of Error Propagation in Classifier Chains for Multi-label Classification
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    Chapter 19 Statistical Comparison of Classifiers for Multi-objective Feature Selection in Instrument Recognition
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    Chapter 20 The Dangers of Using Intention as a Surrogate for Retention in Brand Positioning Decision Support Systems
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    Chapter 21 Multinomial SVM Item Recommender for Repeat-Buying Scenarios
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    Chapter 22 Predicting Changes in Market Segments Based on Customer Behavior
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    Chapter 23 Symbolic Cluster Ensemble based on Co-Association Matrix versus Noisy Variables and Outliers
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    Chapter 24 Image Feature Selection for Market Segmentation: A Comparison of Alternative Approaches
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    Chapter 25 The Validity of Conjoint Analysis: An Investigation of Commercial Studies Over Time
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    Chapter 26 Solving Product Line Design Optimization Problems Using Stochastic Programming
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    Chapter 27 On the Discriminative Power of Credit Scoring Systems Trained on Independent Samples
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    Chapter 28 A Practical Method of Determining Longevity and Premature-Death Risk Aversion in Households and Some Proposals of Its Application
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    Chapter 29 Correlation of Outliers in Multivariate Data
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    Chapter 30 Value-at-Risk Backtesting Procedures Based on Loss Functions: Simulation Analysis of the Power of Tests
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    Chapter 31 Rank Aggregation for Candidate Gene Identification
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    Chapter 32 Unsupervised Dimension Reduction Methods for Protein Sequence Classification
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    Chapter 33 Three Transductive Set Covering Machines
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    Chapter 34 Tone Onset Detection Using an Auditory Model
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    Chapter 35 A Unifying Framework for GPR Image Reconstruction
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    Chapter 36 Recognition of Musical Instruments in Intervals and Chords
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    Chapter 37 ANOVA and Alternatives for Causal Inferences
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    Chapter 38 Testing Models for Medieval Settlement Location
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    Chapter 39 Supporting Selection of Statistical Techniques
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    Chapter 40 Alignment Methods for Folk Tune Classification
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    Chapter 41 Comparing Regression Approaches in Modelling Compensatory and Noncompensatory Judgment Formation
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    Chapter 42 Sensitivity Analyses for the Mixed Coefficients Multinomial Logit Model
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    Chapter 43 Confidence Measures in Automatic Music Classification
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    Chapter 44 Using Latent Class Models with Random Effects for Investigating Local Dependence
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    Chapter 45 The OECD’s Programme for International Student Assessment (PISA) Study: A Review of Its Basic Psychometric Concepts
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    Chapter 46 Music Genre Prediction by Low-Level and High-Level Characteristics
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    Chapter 47 Using Clustering Across Union Catalogues to Enrich Entries with Indexing Information
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    Chapter 48 Text Mining for Ontology Construction
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    Chapter 49 Data Enrichment in Discovery Systems Using Linked Data
Overall attention for this book and its chapters
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Title
Data Analysis, Machine Learning and Knowledge Discovery
Published by
Springer, Cham, January 2014
DOI 10.1007/978-3-319-01595-8
ISBNs
978-3-31-901594-1, 978-3-31-901595-8
Editors

Myra Spiliopoulou, Lars Schmidt-Thieme, Ruth Janning

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 181 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 1%
France 2 1%
United Kingdom 2 1%
Cyprus 1 <1%
Netherlands 1 <1%
Malaysia 1 <1%
Germany 1 <1%
Italy 1 <1%
Brazil 1 <1%
Other 6 3%
Unknown 163 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 44 24%
Researcher 36 20%
Student > Master 34 19%
Student > Bachelor 23 13%
Student > Doctoral Student 8 4%
Other 25 14%
Unknown 11 6%
Readers by discipline Count As %
Computer Science 60 33%
Engineering 30 17%
Business, Management and Accounting 11 6%
Agricultural and Biological Sciences 11 6%
Economics, Econometrics and Finance 9 5%
Other 42 23%
Unknown 18 10%