Advances in intelligent data analysis V : 5th International Symposium on Intelligent Data Analysis, IDA 2003, Berlin, Germany, August 28-30, 2003 : proceedings / Michael R. Berthold [and others] (eds.).

By: (5th : International Symposium on Intelligent Data Analysis (5th : 2003 : Berlin, Germany)
Contributor(s): Berthold, M. (Michael)
Material type: TextTextSeries: SerienbezeichnungLecture notes in computer science: 2810.Publisher: Berlin ; New York : Springer, ©2003Description: 1 online resource (xv, 624 pages) : illustrationsContent type: text Media type: computer Carrier type: online resourceISBN: 9783540452317; 3540452311Other title: IDA 2003Subject(s): Mathematical statistics -- Congresses | Mathematical statistics -- Data processing -- Congresses | Expert systems (Computer science) -- Congresses | Expert systems (Computer science) | Mathematical statistics | Mathematical statistics -- Data processingGenre/Form: Electronic books. | Conference papers and proceedings. Additional physical formats: Print version:: Advances in intelligent data analysis V.DDC classification: 519.5 LOC classification: QA276.A1 | I565 2003Other classification: 54.62 | DAT 703f | MAT 620f | SS 4800 Online resources: Click here to access online
Contents:
Machine Learning -- Pruning for Monotone Classification Trees -- Regularized Learning with Flexible Constraints -- Learning to Answer Emails -- A Semi-supervised Method for Learning the Structure of Robot Environment Interactions -- Using Domain Specific Knowledge for Automated Modeling -- Resolving Rule Conflicts with Double Induction -- A Novel Partial-Memory Learning Algorithm Based on Grey Relational Structure -- Constructing Hierarchical Rule Systems -- Text Categorization Using Hybrid Multiple Model Schemes -- Probability and Topology -- Learning Dynamic Bayesian Networks from Multivariate Time Series with Changing Dependencies -- Topology and Intelligent Data Analysis -- Coherent Conditional Probability as a Measure of Information of the Relevant Conditioning Events -- Very Predictive Ngrams for Space-Limited Probabilistic Models -- Interval Estimation Naïve Bayes -- Mining Networks and Central Entities in Digital Libraries. A Graph Theoretic Approach Applied to Co-author Networks -- Classification and Pattern Recognition -- Learning Linear Classifiers Sensitive to Example Dependent and Noisy Costs -- An Effective Associative Memory for Pattern Recognition -- Similarity Based Classification -- Numerical Attributes in Decision Trees: A Hierarchical Approach -- Similarity-Based Neural Networks for Applications in Computational Molecular Biology -- Combining Pairwise Classifiers with Stacking -- APRIORI-SD: Adapting Association Rule Learning to Subgroup Discovery -- Solving Classification Problems Using Infix Form Genetic Programming -- Clustering -- What Is Fuzzy about Fuzzy Clustering? Understanding and Improving the Concept of the Fuzzifier -- A Mixture Model Approach for Binned Data Clustering -- Fuzzy Clustering Based Segmentation of Time-Series -- An Iterated Local Search Approach for Minimum Sum-of-Squares Clustering -- Data Clustering in Tolerance Space -- Refined Shared Nearest Neighbors Graph for Combining Multiple Data Clusterings -- Clustering Mobile Trajectories for Resource Allocation in Mobile Environments -- Fuzzy Clustering of Short Time-Series and Unevenly Distributed Sampling Points -- Combining and Comparing Cluster Methods in a Receptor Database -- Applications -- Selective Sampling with a Hierarchical Latent Variable Model -- Obtaining Quality Microarray Data via Image Reconstruction -- Large Scale Mining of Molecular Fragments with Wildcards -- Genome-Wide Prokaryotic Promoter Recognition Based on Sequence Alignment Kernel -- Towards Automated Electrocardiac Map Interpretation: An Intelligent Contouring Tool Based on Spatial Aggregation -- Study of Canada/US Dollar Exchange Rate Movements Using Recurrent Neural Network Model of FX-Market -- Gaussian Mixture Density Estimation Applied to Microarray Data -- Classification of Protein Localisation Patterns via Supervised Neural Network Learning -- Applying Intelligent Data Analysis to Coupling Relationships in Object-Oriented Software -- The Smaller the Better: Comparison of Two Approaches for Sales Rate Prediction -- Modeling -- A Multiagent-Based Constructive Approach for Feedforward Neural Networks -- Evolutionary System Identification via Descriptive Takagi Sugeno Fuzzy Systems -- Minimum Message Length Criterion for Second-Order Polynomial Model Selection Applied to Tropical Cyclone Intensity Forecasting -- On the Use of the GTM Algorithm for Mode Detection -- Regularization Methods for Additive Models -- Automated Detection of Influenza Epidemics with Hidden Markov Models -- Guided Incremental Construction of Belief Networks -- Distributed Regression for Heterogeneous Data Sets -- (Data) Preprocessing -- A Logical Formalisation of the Fellegi-Holt Method of Data Cleaning -- Compression Technique Preserving Correlations of a Multivariate Temporal Sequence -- Condensed Representations in Presence of Missing Values -- Measures of Rule Quality for Feature Selection in Text Categorization -- Genetic Approach to Constructive Induction Based on Non-algebraic Feature Representation -- Active Feature Selection Based on a Very Limited Number of Entities.
Summary: This book constitutes the refereed proceedings of the 5th International Conference on Intelligent Data Analysis, IDA 2003, held in Berlin, Germany in August 2003. The 56 revised papers presented were carefully reviewed and selected from 180 submissions. The papers are organized in topical sections on machine learning, probability and topology, classification and pattern recognition, clustering, applications, modeling, and data processing.
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Includes bibliographical references and index.

Machine Learning -- Pruning for Monotone Classification Trees -- Regularized Learning with Flexible Constraints -- Learning to Answer Emails -- A Semi-supervised Method for Learning the Structure of Robot Environment Interactions -- Using Domain Specific Knowledge for Automated Modeling -- Resolving Rule Conflicts with Double Induction -- A Novel Partial-Memory Learning Algorithm Based on Grey Relational Structure -- Constructing Hierarchical Rule Systems -- Text Categorization Using Hybrid Multiple Model Schemes -- Probability and Topology -- Learning Dynamic Bayesian Networks from Multivariate Time Series with Changing Dependencies -- Topology and Intelligent Data Analysis -- Coherent Conditional Probability as a Measure of Information of the Relevant Conditioning Events -- Very Predictive Ngrams for Space-Limited Probabilistic Models -- Interval Estimation Naïve Bayes -- Mining Networks and Central Entities in Digital Libraries. A Graph Theoretic Approach Applied to Co-author Networks -- Classification and Pattern Recognition -- Learning Linear Classifiers Sensitive to Example Dependent and Noisy Costs -- An Effective Associative Memory for Pattern Recognition -- Similarity Based Classification -- Numerical Attributes in Decision Trees: A Hierarchical Approach -- Similarity-Based Neural Networks for Applications in Computational Molecular Biology -- Combining Pairwise Classifiers with Stacking -- APRIORI-SD: Adapting Association Rule Learning to Subgroup Discovery -- Solving Classification Problems Using Infix Form Genetic Programming -- Clustering -- What Is Fuzzy about Fuzzy Clustering? Understanding and Improving the Concept of the Fuzzifier -- A Mixture Model Approach for Binned Data Clustering -- Fuzzy Clustering Based Segmentation of Time-Series -- An Iterated Local Search Approach for Minimum Sum-of-Squares Clustering -- Data Clustering in Tolerance Space -- Refined Shared Nearest Neighbors Graph for Combining Multiple Data Clusterings -- Clustering Mobile Trajectories for Resource Allocation in Mobile Environments -- Fuzzy Clustering of Short Time-Series and Unevenly Distributed Sampling Points -- Combining and Comparing Cluster Methods in a Receptor Database -- Applications -- Selective Sampling with a Hierarchical Latent Variable Model -- Obtaining Quality Microarray Data via Image Reconstruction -- Large Scale Mining of Molecular Fragments with Wildcards -- Genome-Wide Prokaryotic Promoter Recognition Based on Sequence Alignment Kernel -- Towards Automated Electrocardiac Map Interpretation: An Intelligent Contouring Tool Based on Spatial Aggregation -- Study of Canada/US Dollar Exchange Rate Movements Using Recurrent Neural Network Model of FX-Market -- Gaussian Mixture Density Estimation Applied to Microarray Data -- Classification of Protein Localisation Patterns via Supervised Neural Network Learning -- Applying Intelligent Data Analysis to Coupling Relationships in Object-Oriented Software -- The Smaller the Better: Comparison of Two Approaches for Sales Rate Prediction -- Modeling -- A Multiagent-Based Constructive Approach for Feedforward Neural Networks -- Evolutionary System Identification via Descriptive Takagi Sugeno Fuzzy Systems -- Minimum Message Length Criterion for Second-Order Polynomial Model Selection Applied to Tropical Cyclone Intensity Forecasting -- On the Use of the GTM Algorithm for Mode Detection -- Regularization Methods for Additive Models -- Automated Detection of Influenza Epidemics with Hidden Markov Models -- Guided Incremental Construction of Belief Networks -- Distributed Regression for Heterogeneous Data Sets -- (Data) Preprocessing -- A Logical Formalisation of the Fellegi-Holt Method of Data Cleaning -- Compression Technique Preserving Correlations of a Multivariate Temporal Sequence -- Condensed Representations in Presence of Missing Values -- Measures of Rule Quality for Feature Selection in Text Categorization -- Genetic Approach to Constructive Induction Based on Non-algebraic Feature Representation -- Active Feature Selection Based on a Very Limited Number of Entities.

This book constitutes the refereed proceedings of the 5th International Conference on Intelligent Data Analysis, IDA 2003, held in Berlin, Germany in August 2003. The 56 revised papers presented were carefully reviewed and selected from 180 submissions. The papers are organized in topical sections on machine learning, probability and topology, classification and pattern recognition, clustering, applications, modeling, and data processing.

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