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  • 1
    UID:
    gbv_313651051
    Format: XII, 460 S , Ill., graph. Darst
    ISBN: 3540676023
    Series Statement: Lecture notes in computer science 1810
    Note: Literaturangaben
    Additional Edition: Erscheint auch als Online-Ausgabe López de Mántaras, Ramon Machine Learning: ECML 2000 Berlin, Heidelberg : Springer-Verlag Berlin Heidelberg, 2000 ISBN 9783540451648
    Additional Edition: ISBN 3540451641
    Language: English
    Subjects: Computer Science , Economics
    RVK:
    RVK:
    RVK:
    Keywords: Maschinelles Lernen ; Maschinelles Lernen ; Konferenzschrift ; Kongress ; Konferenzschrift
    URL: Cover
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  • 2
    UID:
    b3kat_BV013153299
    Format: XII, 460 S. , Ill., graph. Darst.
    ISBN: 3540676023
    Series Statement: Lecture notes in computer science 1810 : Lecture notes in artificial intelligence
    Language: English
    Subjects: Computer Science
    RVK:
    Keywords: Maschinelles Lernen ; Konferenzschrift
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  • 3
    Book
    Book
    Chichester [u.a.] : Ellis Horwood [u.a.]
    UID:
    gbv_017209412
    Format: 109 S , Ill , 25 cm
    ISBN: 0745802788 , 0470216085
    Series Statement: Ellis Horwood series in artificial intelligence
    Language: English
    Keywords: Künstliche Intelligenz ; Approximatives Schließen ; Unsicherheit ; Expertensystem ; Wahrscheinlichkeit ; Ungewissheit ; Expertensystem
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  • 4
    UID:
    gbv_364796626
    Format: Online-Ressource (XII, 460 S.)
    Edition: Online-Ausg. Springer-11645 Electronic reproduction; Available via World Wide Web
    Edition: Springer eBook Collection. Computer Science
    ISBN: 9783540451648
    Series Statement: Lecture notes in computer science 1810
    Note: Lizenzpflichtig , Electronic reproduction; Available via World Wide Web
    Additional Edition: ISBN 3540676023
    Additional Edition: ISBN 9783540676027
    Language: English
    Keywords: Maschinelles Lernen ; Konferenzschrift
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  • 5
    UID:
    almafu_BV013153299
    Format: XII, 460 S. : Ill., graph. Darst.
    ISBN: 3-540-67602-3
    Series Statement: Lecture notes in computer science 1810 : Lecture notes in artificial intelligence
    Language: English
    Subjects: Computer Science
    RVK:
    Keywords: Maschinelles Lernen ; Konferenzschrift
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  • 6
    UID:
    b3kat_BV010005407
    Format: VI, 616 S. , graph. Darst.
    ISBN: 1558603328
    Language: Undetermined
    Subjects: Computer Science
    RVK:
    Keywords: Unvollkommene Information ; Künstliche Intelligenz ; Konferenzschrift
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  • 7
    UID:
    gbv_1649368666
    Format: Online-Ressource
    ISBN: 9783540451648 , 3540451641
    Series Statement: Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence 1810
    Content: 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.
    Content: The biennial European Conference on Machine Learning (ECML) series is intended to provide an international forum for the discussion of the latest high quality research results in machine learning and is the major European scienti?c event in the ?eld. The eleventh conference (ECML 2000) held in Barcelona, Catalonia, Spain from May 31 to June 2, 2000, has continued this tradition by attracting high quality papers from around the world. Scientists from 21 countries submitted 100 papers to ECML 2000, from which 20 were selected for long oral presentations and 23 for short oral presentations. This selection was based on the recommendations of at least two reviewers for each submitted paper. It is worth noticing that the number of papers reporting applications of machine learning has increased in comparison to past ECML conferences. We believe this fact shows the growing maturity of the ?eld. This volume contains the 43 accepted papers as well as the invited talks by Katharina Morik from the University of Dortmund and Pedro Domingos from the University of Washington at Seattle. In addition, three workshops were jointly organized by ECML 2000 and the European Network of Excellence - net: “Dealing with Structured Data in Machine Learning and Statistics W- stites”, “Machine Learning in the New Information Age” , and “Meta-Learning: Building Automatic Advice Strategies for Model Selection and Method Com- nation”.
    Additional Edition: ISBN 9783540676027
    Additional Edition: Buchausg. u.d.T. Machine learning Berlin : Springer, 2000 ISBN 3540676023
    Language: English
    Subjects: Computer Science , Economics
    RVK:
    RVK:
    RVK:
    Keywords: Maschinelles Lernen ; Maschinelles Lernen ; Konferenzschrift
    URL: Volltext  (lizenzpflichtig)
    URL: Volltext  (lizenzpflichtig)
    URL: Volltext  (lizenzpflichtig)
    URL: Volltext  (lizenzpflichtig)
    URL: Cover
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  • 8
    Book
    Book
    Chichester u.a. :Horwood,
    UID:
    almafu_BV004508445
    Format: 109 S.
    Edition: 1. publ.
    ISBN: 0-7458-0278-8 , 0-470-21608-5
    Series Statement: Ellis Horwood series in artificial intelligence
    Language: English
    Subjects: Computer Science
    RVK:
    Keywords: Künstliche Intelligenz ; Approximatives Schließen ; Unsicherheit ; Expertensystem ; Wahrscheinlichkeit ; Ungewissheit ; Expertensystem
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  • 9
    UID:
    almahu_9947364023702882
    Format: XXIV, 644 p. , online resource.
    ISBN: 9783540749769
    Series Statement: Lecture Notes in Computer Science, 4702
    Content: The two premier annual European conferences in the areas of machine learning and data mining have been collocated ever since the ?rst joint conference in Freiburg, 2001. The European Conference on Machine Learning (ECML) traces its origins to 1986, when the ?rst European Working Session on Learning was held in Orsay, France. The European Conference on Principles and Practice of KnowledgeDiscoveryinDatabases(PKDD) was?rstheldin1997inTrondheim, Norway. Over the years, the ECML/PKDD series has evolved into one of the largest and most selective international conferences in machine learning and data mining. In 2007, the seventh collocated ECML/PKDD took place during September 17–21 on the centralcampus of WarsawUniversityand in the nearby Staszic Palace of the Polish Academy of Sciences. The conference for the third time used a hierarchical reviewing process. We nominated 30 Area Chairs, each of them responsible for one sub-?eld or several closely related research topics. Suitable areas were selected on the basis of the submission statistics for ECML/PKDD 2006 and for last year’s International Conference on Machine Learning (ICML 2006) to ensure a proper load balance amongtheAreaChairs.AjointProgramCommittee(PC)wasnominatedforthe two conferences, consisting of some 300 renowned researchers, mostly proposed by the Area Chairs. This joint PC, the largest of the series to date, allowed us to exploit synergies and deal competently with topic overlaps between ECML and PKDD. ECML/PKDD 2007 received 592 abstract submissions. As in previous years, toassistthereviewersandtheAreaChairsintheir?nalrecommendationauthors had the opportunity to communicate their feedback after the reviewing phase.
    Note: Invited Talks -- Learning, Information Extraction and the Web -- Putting Things in Order: On the Fundamental Role of Ranking in Classification and Probability Estimation -- Mining Queries -- Adventures in Personalized Information Access -- Long Papers -- Experiment Databases: Towards an Improved Experimental Methodology in Machine Learning -- Using the Web to Reduce Data Sparseness in Pattern-Based Information Extraction -- A Graphical Model for Content Based Image Suggestion and Feature Selection -- Efficient AUC Optimization for Classification -- Finding Transport Proteins in a General Protein Database -- Classification of Web Documents Using a Graph-Based Model and Structural Patterns -- Context-Specific Independence Mixture Modelling for Protein Families -- An Algorithm to Find Overlapping Community Structure in Networks -- Privacy Preserving Market Basket Data Analysis -- Feature Extraction from Sensor Data Streams for Real-Time Human Behaviour Recognition -- Generating Social Network Features for Link-Based Classification -- An Empirical Comparison of Exact Nearest Neighbour Algorithms -- Site-Independent Template-Block Detection -- Statistical Model for Rough Set Approach to Multicriteria Classification -- Classification of Anti-learnable Biological and Synthetic Data -- Improved Algorithms for Univariate Discretization of Continuous Features -- Efficient Weight Learning for Markov Logic Networks -- Classification in Very High Dimensional Problems with Handfuls of Examples -- Domain Adaptation of Conditional Probability Models Via Feature Subsetting -- Learning to Detect Adverse Traffic Events from Noisily Labeled Data -- IKNN: Informative K-Nearest Neighbor Pattern Classification -- Finding Outlying Items in Sets of Partial Rankings -- Speeding Up Feature Subset Selection Through Mutual Information Relevance Filtering -- A Comparison of Two Approaches to Classify with Guaranteed Performance -- Towards Data Mining Without Information on Knowledge Structure -- Relaxation Labeling for Selecting and Exploiting Efficiently Non-local Dependencies in Sequence Labeling -- Bridged Refinement for Transfer Learning -- A Prediction-Based Visual Approach for Cluster Exploration and Cluster Validation by HOV3 -- Short Papers -- Flexible Grid-Based Clustering -- Polyp Detection in Endoscopic Video Using SVMs -- A Density-Biased Sampling Technique to Improve Cluster Representativeness -- Expectation Propagation for Rating Players in Sports Competitions -- Efficient Closed Pattern Mining in Strongly Accessible Set Systems (Extended Abstract) -- Discovering Emerging Patterns in Spatial Databases: A Multi-relational Approach -- Realistic Synthetic Data for Testing Association Rule Mining Algorithms for Market Basket Databases -- Learning Multi-dimensional Functions: Gas Turbine Engine Modeling -- Constructing High Dimensional Feature Space for Time Series Classification -- A Dynamic Clustering Algorithm for Mobile Objects -- A Method for Multi-relational Classification Using Single and Multi-feature Aggregation Functions -- MINI: Mining Informative Non-redundant Itemsets -- Stream-Based Electricity Load Forecast -- Automatic Hidden Web Database Classification -- Pruning Relations for Substructure Discovery of Multi-relational Databases -- The Most Reliable Subgraph Problem -- Matching Partitions over Time to Reliably Capture Local Clusters in Noisy Domains -- Searching for Better Randomized Response Schemes for Privacy-Preserving Data Mining -- Pre-processing Large Spatial Data Sets with Bayesian Methods -- Tag Recommendations in Folksonomies -- Providing Naïve Bayesian Classifier-Based Private Recommendations on Partitioned Data -- Multi-party, Privacy-Preserving Distributed Data Mining Using a Game Theoretic Framework -- Multilevel Conditional Fuzzy C-Means Clustering of XML Documents -- Uncovering Fraud in Direct Marketing Data with a Fraud Auditing Case Builder -- Real Time GPU-Based Fuzzy ART Skin Recognition -- A Cooperative Game Theoretic Approach to Prototype Selection -- Dynamic Bayesian Networks for Real-Time Classification of Seismic Signals -- Robust Visual Mining of Data with Error Information -- An Effective Approach to Enhance Centroid Classifier for Text Categorization -- Automatic Categorization of Human-Coded and Evolved CoreWar Warriors -- Utility-Based Regression -- Multi-label Lazy Associative Classification -- Visual Exploration of Genomic Data -- Association Mining in Large Databases: A Re-examination of Its Measures -- Semantic Text Classification of Emergent Disease Reports.
    In: Springer eBooks
    Additional Edition: Printed edition: ISBN 9783540749752
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 10
    UID:
    almahu_9947920563802882
    Format: XII, 472 p. , online resource.
    ISBN: 9783540451648
    Series Statement: Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence, 1810
    Content: The biennial European Conference on Machine Learning (ECML) series is intended to provide an international forum for the discussion of the latest high quality research results in machine learning and is the major European scienti?c event in the ?eld. The eleventh conference (ECML 2000) held in Barcelona, Catalonia, Spain from May 31 to June 2, 2000, has continued this tradition by attracting high quality papers from around the world. Scientists from 21 countries submitted 100 papers to ECML 2000, from which 20 were selected for long oral presentations and 23 for short oral presentations. This selection was based on the recommendations of at least two reviewers for each submitted paper. It is worth noticing that the number of papers reporting applications of machine learning has increased in comparison to past ECML conferences. We believe this fact shows the growing maturity of the ?eld. This volume contains the 43 accepted papers as well as the invited talks by Katharina Morik from the University of Dortmund and Pedro Domingos from the University of Washington at Seattle. In addition, three workshops were jointly organized by ECML 2000 and the European Network of Excellence - net: “Dealing with Structured Data in Machine Learning and Statistics W- stites”, “Machine Learning in the New Information Age” , and “Meta-Learning: Building Automatic Advice Strategies for Model Selection and Method Com- nation”.
    Note: 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.
    In: Springer eBooks
    Additional Edition: Printed edition: ISBN 9783540676027
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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