Machine Learning: ECML 2000 - neues Buch

EAN (ISBN-13): 9783540676027
ISBN (ISBN-10): 3540676023
Gebundene Ausgabe
Taschenbuch
Erscheinungsjahr: 2000
Herausgeber: Springer Berlin Heidelberg
484 Seiten
Gewicht: 0,725 kg
Sprache: eng/Englisch

Buch in der Datenbank seit 2008-02-23T12:22:30+01:00 (Zurich)
Detailseite zuletzt geändert am 2024-02-12T13:09:59+01:00 (Zurich)
ISBN/EAN: 9783540676027

ISBN - alternative Schreibweisen:
3-540-67602-3, 978-3-540-67602-7
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: manta, lopez, pedro domingos, katharina
Titel des Buches: machine learning, barcelona catalonia, european conference artificial intelligence, ecm, lecture notes artificial intelligence, 2000, pro

---

Daten vom Verlag:

Autor/in: Ramon Lopez de Mantaras; Enric Plaza
Titel: Lecture Notes in Computer Science; Lecture Notes in Artificial Intelligence; Machine Learning: ECML 2000 - 11th European Conference on Machine Learning Barcelona, Catalonia, Spain May, 31 - June 2, 2000 Proceedings
Verlag: Springer; Springer Berlin
472 Seiten
Erscheinungsjahr: 2000-05-17
Berlin; Heidelberg; DE
Sprache: Englisch
53,49 € (DE)
54,99 € (AT)
59,00 CHF (CH)
Available
XII, 472 p.

BC; Hardcover, Softcover / Informatik, EDV/Informatik; Datenbanken; Verstehen; Algorithmic Learning; Classification; Data Mining; Decision Diagrams; Inductive Learning; Inductive Logic Programming; Inference; algorithms; cognition; complexity; genetic algorithms; knowledge discovery; learning; machine learning; proving; algorithm analysis and problem complexity; Database Management; Artificial Intelligence; Algorithms; Künstliche Intelligenz; Algorithmen und Datenstrukturen; EA

Invited Papers.- Beyond Occam’s Razor: Process-Oriented Evaluation.- The Representation Race — Preprocessing for Handling Time Phenomena.- Contributed Papers.- Short-Term Profiling for a Case-Based Reasoning Recommendation System.- K-SVCR. A Multi-class Support Vector Machine.- Learning Trading Rules with Inductive Logic Programming.- Improving Knowledge Discovery Using Domain Knowledge in Unsupervised Learning.- Exploiting Classifier Combination for Early Melanoma Diagnosis Support.- A Comparison of Ranking Methods for Classification Algorithm Selection.- Hidden Markov Models with Patterns and Their Application to Integrated Circuit Testing.- Comparing Complete and Partial Classification for Identifying Latently Dissatisfied Customers.- Wrapper Generation via Grammar Induction.- Diversity versus Quality in Classification Ensembles Based on Feature Selection.- Minimax TD-Learning with Neural Nets in a Markov Game.- Boosting Applied to Word Sense Disambiguation.- A Multiple Model Cost-Sensitive Approach for Intrusion Detection.- Value Miner: A Data Mining Environment for the Calculation of the Customer Lifetime Value with Application to the Automotive Industry.- Investigation and Reduction of Discretization Variance in Decision Tree Induction.- Asymmetric Co-evolution for Imperfect-Information Zero-Sum Games.- A Machine Learning Approach to Workflow Management.- The Utilization of Context Signals in the Analysis of ABR Potentials by Application of Neural Networks.- Complexity Approximation Principle and Rissanen’s Approach to Real-Valued Parameters.- Handling Continuous-Valued Attributes in Decision Tree with Neural Network Modeling.- Learning Context-Free Grammars with a Simplicity Bias.- Partially Supervised Text Classification: Combining Labeled and Unlabeled Documents Using an EM-like Scheme.- Toward an Explanatory Similarity Measure for Nearest-Neighbor Classification.- Relative Unsupervised Discretization for Regression Problems.- Metric-Based Inductive Learning Using Semantic Height Functions.- Error Analysis of Automatic Speech Recognition Using Principal Direction Divisive Partitioning.- A Study on the Performance of Large Bayes Classifier.- Dynamic Discretization of Continuous Values from Time Series.- Using a Symbolic Machine Learning Tool to Refine Lexico-syntactic Patterns.- Measuring Performance when Positives Are Rare: Relative Advantage versus Predictive Accuracy — A Biological Case-Study.- Mining TCP/IP Traffic for Network Intrusion Detection by Using a Distributed Genetic Algorithm.- Learning Patterns of Behavior by Observing System Events.- Dimensionality Reduction through Sub-space Mapping for Nearest Neighbour Algorithms.- Nonparametric Regularization of Decision Trees.- An Efficient and Effective Procedure for Updating a Competence Model for Case-Based Reasoners.- Layered Learning.- Problem Decomposition for Behavioural Cloning.- Dynamic Feature Selection in Incremental Hierarchical Clustering.- On the Boosting Pruning Problem.- An Empirical Study of MetaCost Using Boosting Algorithms.- Clustered Partial Linear Regression.- Knowledge Discovery from Very Large Databases Using Frequent Concept Lattices.- Some Improvements on Event-Sequence Temporal Region Methods.
Includes supplementary material: sn.pub/extras