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Advances in Intelligent Data Analysis VIII [[electronic resource] ] : 8th International Symposium on Intelligent Data Analysis, IDA 2009, Lyon, France, August 31 - September 2, 2009, Proceedings / / edited by Niall M. Adams, Céline Robardet, Arno Siebes, Jean-Francois Boulicaut
| Advances in Intelligent Data Analysis VIII [[electronic resource] ] : 8th International Symposium on Intelligent Data Analysis, IDA 2009, Lyon, France, August 31 - September 2, 2009, Proceedings / / edited by Niall M. Adams, Céline Robardet, Arno Siebes, Jean-Francois Boulicaut |
| Edizione | [1st ed. 2009.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2009 |
| Descrizione fisica | 1 online resource (XIII, 418 p.) |
| Disciplina | 006.31222gerDNB |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Computers
Information storage and retrieval Data mining Pattern recognition Data structures (Computer science) Information technology Business—Data processing Theory of Computation Information Storage and Retrieval Data Mining and Knowledge Discovery Pattern Recognition Data Structures IT in Business |
| Soggetto genere / forma |
Kongress.
Lyon (2008) |
| ISBN | 3-642-03915-4 |
| Classificazione |
DAT 703f
MAT 620f SS 4800 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Invited Papers -- Intelligent Data Analysis in the 21st Century -- Analyzing the Localization of Retail Stores with Complex Systems Tools -- Selected Contributions 1 (Long Talks) -- Change (Detection) You Can Believe in: Finding Distributional Shifts in Data Streams -- Exploiting Data Missingness in Bayesian Network Modeling -- DEMScale: Large Scale MDS Accounting for a Ridge Operator and Demographic Variables -- How to Control Clustering Results? Flexible Clustering Aggregation -- Compensation of Translational Displacement in Time Series Clustering Using Cross Correlation -- Context-Based Distance Learning for Categorical Data Clustering -- Semi-supervised Text Classification Using RBF Networks -- Improving k-NN for Human Cancer Classification Using the Gene Expression Profiles -- Subgroup Discovery for Test Selection: A Novel Approach and Its Application to Breast Cancer Diagnosis -- Trajectory Voting and Classification Based on Spatiotemporal Similarity in Moving Object Databases -- Leveraging Call Center Logs for Customer Behavior Prediction -- Condensed Representation of Sequential Patterns According to Frequency-Based Measures -- ART-Based Neural Networks for Multi-label Classification -- Two-Way Grouping by One-Way Topic Models -- Selecting and Weighting Data for Building Consensus Gene Regulatory Networks -- Incremental Bayesian Network Learning for Scalable Feature Selection -- Feature Extraction and Selection from Vibration Measurements for Structural Health Monitoring -- Zero-Inflated Boosted Ensembles for Rare Event Counts -- Selected Contributions 2 (Short Talks) -- Mining the Temporal Dimension of the Information Propagation -- Adaptive Learning from Evolving Data Streams -- An Application of Intelligent Data Analysis Techniques to a Large Software Engineering Dataset -- Which Distance for the Identification and the Differentiation of Cell-Cycle Expressed Genes? -- Ontology-Driven KDD Process Composition -- Mining Frequent Gradual Itemsets from Large Databases -- Selecting Computer Architectures by Means of Control-Flow-Graph Mining -- Visualization-Driven Structural and Statistical Analysis of Turbulent Flows -- Distributed Algorithm for Computing Formal Concepts Using Map-Reduce Framework -- Multi-Optimisation Consensus Clustering -- Improving Time Series Forecasting by Discovering Frequent Episodes in Sequences -- Measure of Similarity and Compactness in Competitive Space -- Bayesian Solutions to the Label Switching Problem -- Efficient Vertical Mining of Frequent Closures and Generators -- Isotonic Classification Trees. |
| Record Nr. | UNISA-996465760203316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2009 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Constraint-Based Mining and Inductive Databases [[electronic resource] ] : European Workshop on Inductive Databases and Constraint Based Mining, Hinterzarten, Germany, March 11-13, 2004, Revised Selected Papers / / edited by Jean-Francois Boulicaut, Luc De Raedt, Heikki Mannila
| Constraint-Based Mining and Inductive Databases [[electronic resource] ] : European Workshop on Inductive Databases and Constraint Based Mining, Hinterzarten, Germany, March 11-13, 2004, Revised Selected Papers / / edited by Jean-Francois Boulicaut, Luc De Raedt, Heikki Mannila |
| Edizione | [1st ed. 2006.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2006 |
| Descrizione fisica | 1 online resource (X, 404 p.) |
| Disciplina | 005.74 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Computers Database management Information storage and retrieval Pattern recognition Artificial Intelligence Computation by Abstract Devices Database Management Information Storage and Retrieval Pattern Recognition |
| ISBN | 3-540-31351-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | The Hows, Whys, and Whens of Constraints in Itemset and Rule Discovery -- A Relational Query Primitive for Constraint-Based Pattern Mining -- To See the Wood for the Trees: Mining Frequent Tree Patterns -- A Survey on Condensed Representations for Frequent Sets -- Adaptive Strategies for Mining the Positive Border of Interesting Patterns: Application to Inclusion Dependencies in Databases -- Computation of Mining Queries: An Algebraic Approach -- Inductive Queries on Polynomial Equations -- Mining Constrained Graphs: The Case of Workflow Systems -- CrossMine: Efficient Classification Across Multiple Database Relations -- Remarks on the Industrial Application of Inductive Database Technologies -- How to Quickly Find a Witness -- Relevancy in Constraint-Based Subgroup Discovery -- A Novel Incremental Approach to Association Rules Mining in Inductive Databases -- Employing Inductive Databases in Concrete Applications -- Contribution to Gene Expression Data Analysis by Means of Set Pattern Mining -- Boolean Formulas and Frequent Sets -- Generic Pattern Mining Via Data Mining Template Library -- Inductive Querying for Discovering Subgroups and Clusters. |
| Record Nr. | UNISA-996466097903316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Discovery Science [[electronic resource] ] : 11th International Conference, DS 2008, Budapest, Hungary, October 13-16, 2008, Proceedings / / edited by Jean-Francois Boulicaut, Michael R. Berthold, Tamás Horváth
| Discovery Science [[electronic resource] ] : 11th International Conference, DS 2008, Budapest, Hungary, October 13-16, 2008, Proceedings / / edited by Jean-Francois Boulicaut, Michael R. Berthold, Tamás Horváth |
| Edizione | [1st ed. 2008.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2008 |
| Descrizione fisica | 1 online resource (XII, 348 p. 96 illus.) |
| Disciplina | 501 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Data mining Database management Information storage and retrieval Application software Artificial Intelligence Data Mining and Knowledge Discovery Database Management Information Storage and Retrieval Computer Appl. in Administrative Data Processing Computer Appl. in Social and Behavioral Sciences |
| ISBN | 3-540-88411-4 |
| Classificazione | 54.72 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Invited Papers -- On Iterative Algorithms with an Information Geometry Background -- Visual Analytics: Combining Automated Discovery with Interactive Visualizations -- Some Mathematics Behind Graph Property Testing -- Finding Total and Partial Orders from Data for Seriation -- Computational Models of Neural Representations in the Human Brain -- Learning -- Unsupervised Classifier Selection Based on Two-Sample Test -- An Empirical Investigation of the Trade-Off between Consistency and Coverage in Rule Learning Heuristics -- Learning Model Trees from Data Streams -- Empirical Asymmetric Selective Transfer in Multi-objective Decision Trees -- Ensemble-Trees: Leveraging Ensemble Power Inside Decision Trees -- A Comparison between Neural Network Methods for Learning Aggregate Functions -- Feature Selection -- Smoothed Prediction of the Onset of Tree Stem Radius Increase Based on Temperature Patterns -- Feature Selection in Taxonomies with Applications to Paleontology -- Associations -- Deduction Schemes for Association Rules -- Constructing Iceberg Lattices from Frequent Closures Using Generators -- Discovery Processes -- Learning from Each Other -- Comparative Evaluation of Two Systems for the Visual Navigation of Encyclopedia Knowledge Spaces -- A Framework for Knowledge Discovery in a Society of Agents -- Learning and Chemistry -- Active Learning for High Throughput Screening -- An Efficiently Computable Graph-Based Metric for the Classification of Small Molecules -- Mining Intervals of Graphs to Extract Characteristic Reaction Patterns -- Clustering -- Refining Pairwise Similarity Matrix for Cluster Ensemble Problem with Cluster Relations -- Input Noise Robustness and Sensitivity Analysis to Improve Large Datasets Clustering by Using the GRID -- An Integrated Graph and Probability Based Clustering Framework for Sequential Data -- Cluster Analysis in Remote Sensing Spectral Imagery through Graph Representation and Advanced SOM Visualization -- Structured Data -- Mining Unordered Distance-Constrained Embedded Subtrees -- Finding Frequent Patterns from Compressed Tree-Structured Data -- A Modeling Approach Using Multiple Graphs for Semi-Supervised Learning -- Text Analysis -- String Kernels Based on Variable-Length-Don’t-Care Patterns -- Unsupervised Spam Detection by Document Complexity Estimation -- A Probabilistic Neighbourhood Translation Approach for Non-standard Text Categorisation. |
| Record Nr. | UNISA-996466127703316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Knowledge Discovery in Databases: PKDD 2004 [[electronic resource] ] : 8th European Conference on Principles and Practice of Knowledge Discovery in Databases, Pisa, Italy, September 20-24, 2004, Proceedings / / edited by Jean-Francois Boulicaut, Floriana Esposito, Fosca Giannotti, Dino Pedreschi
| Knowledge Discovery in Databases: PKDD 2004 [[electronic resource] ] : 8th European Conference on Principles and Practice of Knowledge Discovery in Databases, Pisa, Italy, September 20-24, 2004, Proceedings / / edited by Jean-Francois Boulicaut, Floriana Esposito, Fosca Giannotti, Dino Pedreschi |
| Edizione | [1st ed. 2004.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2004 |
| Descrizione fisica | 1 online resource (XIX, 562 p.) |
| Disciplina | 006.312 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Data structures (Computer science) Database management Information storage and retrieval Mathematical statistics Natural language processing (Computer science) Artificial Intelligence Data Structures and Information Theory Database Management Information Storage and Retrieval Probability and Statistics in Computer Science Natural Language Processing (NLP) |
| ISBN | 3-540-30116-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Invited Papers -- Random Matrices in Data Analysis -- Data Privacy -- Breaking Through the Syntax Barrier: Searching with Entities and Relations -- Real-World Learning with Markov Logic Networks -- Strength in Diversity: The Advance of Data Analysis -- Contributed Papers -- Mining Positive and Negative Association Rules: An Approach for Confined Rules -- An Experiment on Knowledge Discovery in Chemical Databases -- Shape and Size Regularization in Expectation Maximization and Fuzzy Clustering -- Combining Multiple Clustering Systems -- Reducing Data Stream Sliding Windows by Cyclic Tree-Like Histograms -- A Framework for Data Mining Pattern Management -- Spatial Associative Classification at Different Levels of Granularity: A Probabilistic Approach -- AutoPart: Parameter-Free Graph Partitioning and Outlier Detection -- Properties and Benefits of Calibrated Classifiers -- A Tree-Based Approach to Clustering XML Documents by Structure -- Discovery of Regulatory Connections in Microarray Data -- Learning from Little: Comparison of Classifiers Given Little Training -- Geometric and Combinatorial Tiles in 0–1 Data -- Document Classification Through Interactive Supervision of Document and Term Labels -- Classifying Protein Fingerprints -- Finding Interesting Pass Patterns from Soccer Game Records -- Discovering Unexpected Information for Technology Watch -- Scalable Density-Based Distributed Clustering -- Summarization of Dynamic Content in Web Collections -- Mining Thick Skylines over Large Databases -- Ensemble Feature Ranking -- Privately Computing a Distributed k-nn Classifier -- Incremental Nonlinear PCA for Classification -- A Spectroscopy of Texts for Effective Clustering -- Constraint-Based Mining of Episode Rules and Optimal Window Sizes -- Analysing Customer Churn in Insurance Data – A Case Study -- Nomograms for Visualization of Naive Bayesian Classifier -- Using a Hash-Based Method for Apriori-Based Graph Mining -- Evaluation of Rule Interestingness Measures with a Clinical Dataset on Hepatitis -- Classification in Geographical Information Systems -- Digging into Acceptor Splice Site Prediction: An Iterative Feature Selection Approach -- Itemset Classified Clustering -- Combining Winnow and Orthogonal Sparse Bigrams for Incremental Spam Filtering -- Asynchronous and Anticipatory Filter-Stream Based Parallel Algorithm for Frequent Itemset Mining -- A Quantification of Cluster Novelty with an Application to Martian Topography -- Density-Based Spatial Clustering in the Presence of Obstacles and Facilitators -- Text Mining for Finding Functional Community of Related Genes Using TCM Knowledge -- Dealing with Predictive-but-Unpredictable Attributes in Noisy Data Sources -- A New Scheme on Privacy Preserving Association Rule Mining -- Posters -- A Unified and Flexible Framework for Comparing Simple and Complex Patterns -- Constructing (Almost) Phylogenetic Trees from Developmental Sequences Data -- Learning from Multi-source Data -- The Anatomy of SnakeT: A Hierarchical Clustering Engine for Web-Page Snippets -- COCOA: Compressed Continuity Analysis for Temporal Databases -- Discovering Interpretable Muscle Activation Patterns with the Temporal Data Mining Method -- A Tolerance Rough Set Approach to Clustering Web Search Results -- Improving the Performance of the RISE Algorithm -- Mining History of Changes to Web Access Patterns -- Demonstration Papers -- Visual Mining of Spatial Time Series Data -- Detecting Driving Awareness -- An Effective Recommender System for Highly Dynamic and Large Web Sites -- SemanticTalk: Software for Visualizing Brainstorming Sessions and Thematic Concept Trails on Document Collections -- Orange: From Experimental Machine Learning to Interactive Data Mining -- Terrorist Detection System -- Experimenting SnakeT: A Hierarchical Clustering Engine for Web-Page Snippets -- HIClass: Hyper-interactive Text Classification by Interactive Supervision of Document and Term Labels -- Balios – The Engine for Bayesian Logic Programs -- SEWeP: A Web Mining System Supporting Semantic Personalization -- SPIN! Data Mining System Based on Component Architecture. |
| Record Nr. | UNISA-996465661603316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Knowledge Discovery in Inductive Databases [[electronic resource] ] : 4th International Workshop, KDID 2005, Porto, Portugal, October 3, 2005, Revised Selected and Invited Papers / / edited by Francesco Bonchi, Jean-Francois Boulicaut
| Knowledge Discovery in Inductive Databases [[electronic resource] ] : 4th International Workshop, KDID 2005, Porto, Portugal, October 3, 2005, Revised Selected and Invited Papers / / edited by Francesco Bonchi, Jean-Francois Boulicaut |
| Edizione | [1st ed. 2006.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2006 |
| Descrizione fisica | 1 online resource (VIII, 252 p.) |
| Disciplina | 005.74 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Data structures (Computer science)
Database management Artificial intelligence Data Structures and Information Theory Database Management Artificial Intelligence |
| ISBN | 3-540-33293-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Invited Papers -- Data Mining in Inductive Databases -- Mining Databases and Data Streams with Query Languages and Rules -- Contributed Papers -- Memory-Aware Frequent k-Itemset Mining -- Constraint-Based Mining of Fault-Tolerant Patterns from Boolean Data -- Experiment Databases: A Novel Methodology for Experimental Research -- Quick Inclusion-Exclusion -- Towards Mining Frequent Queries in Star Schemes -- Inductive Databases in the Relational Model: The Data as the Bridge -- Transaction Databases, Frequent Itemsets, and Their Condensed Representations -- Multi-class Correlated Pattern Mining -- Shaping SQL-Based Frequent Pattern Mining Algorithms -- Exploiting Virtual Patterns for Automatically Pruning the Search Space -- Constraint Based Induction of Multi-objective Regression Trees -- Learning Predictive Clustering Rules. |
| Record Nr. | UNISA-996466100803316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Local Pattern Detection [[electronic resource] ] : International Seminar Dagstuhl Castle, Germany, April 12-16, 2004, Revised Selected Papers / / edited by Katharina Morik, Jean-Francois Boulicaut, Arno Siebes
| Local Pattern Detection [[electronic resource] ] : International Seminar Dagstuhl Castle, Germany, April 12-16, 2004, Revised Selected Papers / / edited by Katharina Morik, Jean-Francois Boulicaut, Arno Siebes |
| Edizione | [1st ed. 2005.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2005 |
| Descrizione fisica | 1 online resource (XI, 233 p.) |
| Disciplina | 006.3/12 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Data structures (Computer science) Algorithms Mathematical statistics Database management Information storage and retrieval Artificial Intelligence Data Structures and Information Theory Algorithm Analysis and Problem Complexity Probability and Statistics in Computer Science Database Management Information Storage and Retrieval |
| ISBN | 9783540318941 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Pushing Constraints to Detect Local Patterns -- From Local to Global Patterns: Evaluation Issues in Rule Learning Algorithms -- Pattern Discovery Tools for Detecting Cheating in Student Coursework -- Local Pattern Detection and Clustering -- Local Patterns: Theory and Practice of Constraint-Based Relational Subgroup Discovery -- Visualizing Very Large Graphs Using Clustering Neighborhoods -- Features for Learning Local Patterns in Time-Stamped Data -- Boolean Property Encoding for Local Set Pattern Discovery: An Application to Gene Expression Data Analysis -- Local Pattern Discovery in Array-CGH Data -- Learning with Local Models -- Knowledge-Based Sampling for Subgroup Discovery -- Temporal Evolution and Local Patterns -- Undirected Exception Rule Discovery as Local Pattern Detection -- From Local to Global Analysis of Music Time Series. |
| Record Nr. | UNISA-996466161503316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2005 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Machine Learning: ECML 2004 [[electronic resource] ] : 15th European Conference on Machine Learning, Pisa, Italy, September 20-24, 2004, Proceedings / / edited by Jean-Francois Boulicaut, Floriana Esposito, Fosca Giannotti, Dino Pedreschi
| Machine Learning: ECML 2004 [[electronic resource] ] : 15th European Conference on Machine Learning, Pisa, Italy, September 20-24, 2004, Proceedings / / edited by Jean-Francois Boulicaut, Floriana Esposito, Fosca Giannotti, Dino Pedreschi |
| Edizione | [1st ed. 2004.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2004 |
| Descrizione fisica | 1 online resource (XVIII, 582 p.) |
| Disciplina | 006.31 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Algorithms Mathematical logic Database management Artificial Intelligence Algorithm Analysis and Problem Complexity Mathematical Logic and Formal Languages Database Management |
| ISBN | 3-540-30115-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Invited Papers -- Random Matrices in Data Analysis -- Data Privacy -- Breaking Through the Syntax Barrier: Searching with Entities and Relations -- Real-World Learning with Markov Logic Networks -- Strength in Diversity: The Advance of Data Analysis -- Contributed Papers -- Filtered Reinforcement Learning -- Applying Support Vector Machines to Imbalanced Datasets -- Sensitivity Analysis of the Result in Binary Decision Trees -- A Boosting Approach to Multiple Instance Learning -- An Experimental Study of Different Approaches to Reinforcement Learning in Common Interest Stochastic Games -- Learning from Message Pairs for Automatic Email Answering -- Concept Formation in Expressive Description Logics -- Multi-level Boundary Classification for Information Extraction -- An Analysis of Stopping and Filtering Criteria for Rule Learning -- Adaptive Online Time Allocation to Search Algorithms -- Model Approximation for HEXQ Hierarchical Reinforcement Learning -- Iterative Ensemble Classification for Relational Data: A Case Study of Semantic Web Services -- Analyzing Multi-agent Reinforcement Learning Using Evolutionary Dynamics -- Experiments in Value Function Approximation with Sparse Support Vector Regression -- Constructive Induction for Classifying Time Series -- Fisher Kernels for Logical Sequences -- The Enron Corpus: A New Dataset for Email Classification Research -- Margin Maximizing Discriminant Analysis -- Multi-objective Classification with Info-Fuzzy Networks -- Improving Progressive Sampling via Meta-learning on Learning Curves -- Methods for Rule Conflict Resolution -- An Efficient Method to Estimate Labelled Sample Size for Transductive LDA(QDA/MDA) Based on Bayes Risk -- Analyzing Sensory Data Using Non-linear Preference Learning with Feature Subset Selection -- Dynamic Asset Allocation Exploiting Predictors in Reinforcement Learning Framework -- Justification-Based Selection of Training Examples for Case Base Reduction -- Using Feature Conjunctions Across Examples for Learning Pairwise Classifiers -- Feature Selection Filters Based on the Permutation Test -- Sparse Distributed Memories for On-Line Value-Based Reinforcement Learning -- Improving Random Forests -- The Principal Components Analysis of a Graph, and Its Relationships to Spectral Clustering -- Using String Kernels to Identify Famous Performers from Their Playing Style -- Associative Clustering -- Learning to Fly Simple and Robust -- Bayesian Network Methods for Traffic Flow Forecasting with Incomplete Data -- Matching Model Versus Single Model: A Study of the Requirement to Match Class Distribution Using Decision Trees -- Inducing Polynomial Equations for Regression -- Efficient Hyperkernel Learning Using Second-Order Cone Programming -- Effective Voting of Heterogeneous Classifiers -- Convergence and Divergence in Standard and Averaging Reinforcement Learning -- Document Representation for One-Class SVM -- Naive Bayesian Classifiers for Ranking -- Conditional Independence Trees -- Exploiting Unlabeled Data in Content-Based Image Retrieval -- Population Diversity in Permutation-Based Genetic Algorithm -- Simultaneous Concept Learning of Fuzzy Rules -- Posters -- SWITCH: A Novel Approach to Ensemble Learning for Heterogeneous Data -- Estimating Attributed Central Orders -- Batch Reinforcement Learning with State Importance -- Explicit Local Models: Towards “Optimal” Optimization Algorithms -- An Intelligent Model for the Signorini Contact Problem in Belt Grinding Processes -- Cluster-Grouping: From Subgroup Discovery to Clustering. |
| Record Nr. | UNISA-996465310603316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||