- Some Experimental Results on Learning Probabilistic and Possibilistic Networks with
- 17 FuzzyMethoden in der Datenanalyse Christian Borgelt 1 , J org Gebhardt 2 und Rudolf Kruse 3
- Possibilistic Networks: Data Mining Applications Rudolf Kruse and Christian Borgelt
- Fuzzy and Probabilistic Clustering with Shape and Size Constraints
- Mining Fragments with Fuzzy Chains in Molecular Databases
- Advanced Pruning Strategies to Speed Up Mining Closed Molecular Fragments
- Fuzzy Cluster Analysis with Cluster Repulsion Heiko Timm, Christian Borgelt, and Rudolf Kruse
- Possibilistic Graphical Models Christian Borgelt, Jorg Gebhardt, and Rudolf Kruse
- Minimum Weight Triangulation by Cutting Out Triangles
- Experiments in Term Weighting and Keyword Extraction in Document Clustering
- SaM: A Split and Merge Algorithm for Fuzzy Frequent Item Set Mining Christian Borgelt 1 and Xiaomeng Wang 2
- Learning Graphical Models by Extending Optimal Spanning Trees
- On Canonical Forms for Frequent Graph Mining Christian Borgelt
- A Decision Tree PlugIn for DataEngine tm Christian Borgelt
- Data Mining mit NeuroFuzzySystemen Rudolf Kruse, Christian Borgelt und Detlef Nauck
- CHRISTIAN BORGELT AND RUDOLF KRUSE ABDUCTIVE INFERENCE
- A Naive Bayes Classifier PlugIn for DataEngine tm Christian Borgelt
- Efficient Implementations of Apriori and Eclat Christian Borgelt
- Data Mining with Graphical Models Rudolf Kruse and Christian Borgelt
- Fuzzy Data Analysis: Challenges and Perspectives Rudolf Kruse, Christian Borgelt, and Detlef Nauck
- IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. XX, NO. Y, MONTH YEAR 1 Learning Possibilistic Graphical Models from Data
- MoSS: A Program for Molecular Substructure Mining Christian Borgelt
- Attributauswahlmae f ur die Induktion von Entscheidungsb aumen: Ein
- Speeding Up Fuzzy Clustering with Neural Network Techniques
- A Conditional Independence Algorithm for Learning Undirected Graphical Models
- Discriminative Closed Fragment Mining and Perfect Extensions MoFa
- Finding Closed Frequent Item Sets by Intersecting Transactions
- Fixed Parameter Algorithms for the Minimum Weight Triangulation Problem
- Data Mining with Graphical Models Dissertation
- Advanced Fuzzy Clustering and Decision Tree Plug-Ins for DataEnginetm
- Full Perfect Extension Pruning for Frequent Graph Mining Christian Borgelt
- Canonical Forms for Frequent Graph Mining Christian Borgelt
- FrIDA --A Free Intelligent Data Analysis Toolbox Christian Borgelt and Gil Gonzalez Rodriguez
- 17 Fuzzy-Methoden in der Datenanalyse Christian Borgelt1
- Data Mining mit Neuro-Fuzzy-Systemen Rudolf Kruse, Christian Borgelt und Detlef Nauck
- LEARNING VECTOR QUANTIZATION: CLUSTER SIZE AND CLUSTER NUMBER Christian Borgelt
- Fuzzy Frequent Item Set Mining based on Recursive Elimination Xiaomeng Wang, Christian Borgelt and Rudolf Kruse
- A Naive Bayes Style Possibilistic Classifier Christian Borgelt and Jorg Gebhardt
- Probabilistic Networks and Fuzzy Clustering as Generalizations of Naive Bayes Classifiers
- Mining Fuzzy Frequent Item Sets Xiaomeng Wang, Christian Borgelt, and Rudolf Kruse
- Simple Algorithms for Frequent Item Set Mining Christian Borgelt
- Efficient Maximum Projection of Database-Induced Multivariate Possibility Distributions
- Fixed Parameter Algorithms for Minimum Weight Partitions Christian Borgelt + , Magdalene Grantson # , and Christos Levcopoulos #
- Lernen probabilistischer und possibilistischer Netze aus Daten: Theorie und Anwendung
- Christian Borgelt und Rudolf Kruse Probabilistische graphische Modelle
- Information Mining Rudolf Kruse and Christian Borgelt
- Some Experimental Results on Learning Probabilistic and Possibilistic Networks with
- Finding the Number of Fuzzy Clusters by Resampling
- Data Mining with Graphical Models Dissertation
- The Role of Soft Computing in Intelligent Data Analysis (Invited Paper)
- Mining Molecular Fragments: Finding Relevant Substructures of Molecules
- A Decision Tree Plug-In for DataEnginetm Christian Borgelt
- SaM: A Split and Merge Algorithm for Fuzzy Frequent Item Set Mining Christian Borgelt
- A Naive Bayes Classifier Plug-In for DataEnginetm Christian Borgelt
- Resampling for Fuzzy Clustering Christian Borgelt
- Using Fuzzy Clustering to Improve Naive Bayes Classifiers and Probabilistic Networks
- IDENTIFICATION OF NEURONS PARTICIPATING IN CELL ASSEMBLIES Sonja Gr un 1,2 , Denise Berger 2,3 , and Christian Borgelt 4
- Problems and Prospects in Fuzzy Data Analysis Rudolf Kruse 1 , Christian Borgelt 1 , and Detlef Nauck 2
- Experiments in Document Clustering using Cluster Specific Term Weights
- An Extended Objective Function for Prototypeless Fuzzy Clustering
- Hindawi Publishing Corporation Computational Intelligence and Neuroscience
- Fast Fuzzy Clustering of Web Page Collections Christian Borgelt and Andreas Nurnberger
- Keeping Things Simple: Finding Frequent Item Sets by Recursive Elimination
- Learning Possibilistic Networks with a Global Evaluation Method Christian Borgelt
- Fuzzy Learning Vector Quantization with Size and Shape Parameters
- A Fixed Parameter Algorithm for Minimum Weight Triangulation
- Mining Fuzzy Frequent Item Sets Xiaomeng Wang, Christian Borgelt, and Rudolf Kruse
- Prototypeless Fuzzy Clustering Christian Borgelt
- Molecular Fragment Mining for Drug Discovery Christian Borgelt 1 , Michael R. Berthold 2 , and David E. Patterson 2
- On Identifying TreeStructured Perfect Maps Christian Borgelt
- Fuzzy Subspace Clustering Christian Borgelt
- Fast Fuzzy Clustering of Web Page Collections Christian Borgelt and Andreas Nurnberger
- Learning Graphical Models by Extending Optimal Spanning Trees
- IDENTIFICATION OF NEURONS PARTICIPATING IN CELL ASSEMBLIES Sonja Grun1,2
- Learning from Imprecise Data: Possibilistic Graphical Models
- Learning Probabilistic and Possibilistic Networks: Theory and Applications Rudolf Kruse and Christian Borgelt
- Einf uhrung in Datenanalyse und Data Mining mit intelligenten Technologien
- Christian Borgelt und Rudolf Kruse Probabilistische graphische Modelle
- Learning Undirected Possibilistic Networks with Conditional Independence Tests
- Evaluation Measures for Learning Probabilistic and Possibilistic Networks
- Mining Fragments with Fuzzy Chains in Molecular Databases
- Information Measures in Fuzzy Decision Trees Xiaomeng Wang
- Neue Entwicklungen im Data Mining mit Bayesschen Netzen Rudolf Kruse und Christian Borgelt
- Graph Mining: Repository vs. Canonical Form Christian Borgelt and Mathias Fiedler
- Notes on the Dynamic Bichromatic AllNearestNeighbors Problem Magdalene G. Borgelt # Christian Borgelt +
- Naive Bayes Classifiers Using NeuroFuzzy Learning 1
- Resampling for Fuzzy Clustering Christian Borgelt
- Graph Mining: An Overview Christian Borgelt
- Abductive Inference with Probabilistic Graphical Models
- Information Measures in Fuzzy Decision Trees Xiaomeng Wang
- F1.2 Inference Methods C Borgelt 1 , J Gebhardt 2 , and R Kruse 1
- Canonical Forms for Frequent Graph Mining Christian Borgelt
- LEARNING VECTOR QUANTIZATION: CLUSTER SIZE AND CLUSTER NUMBER Christian Borgelt
- October 7, 2009 11:25 WSPC/Guidelines ijcga08 Fixed Parameter Algorithms for the
- Recursion Pruning for the Apriori Algorithm Christian Borgelt
- Data Mining with Possibilistic Graphical Models
- Fuzzy and Probabilistic Clustering with Shape and Size Constraints
- Possibilistic Networks with Local Structure Christian Borgelt and Rudolf Kruse
- Finding Discriminative Molecular Fragments Christian Borgelt 1 , Heiko Hofer 2 , and Michael Berthold 2
- Advanced Fuzzy Clustering and Decision Tree PlugIns for DataEngine tm
- Evaluation Measures for Learning Probabilistic and Possibilistic Networks
- Concepts for Probabilistic and Possibilistic Induction of Decision Trees on Real World Data
- Fuzzy Cluster Analysis with Cluster Repulsion Heiko Timm, Christian Borgelt, and Rudolf Kruse
- Learning Undirected Possibilistic Networks with Conditional Independence Tests
- Efficient Implementations of Apriori and Eclat Christian Borgelt
- Selecting the Links in BisoNets Generated from Document Collections
- Effects of Irrelevant Attributes in Fuzzy Clustering Christian Doring, Christian Borgelt, and Rudolf Kruse
- FrIDA ---A Free Intelligent Data Analysis Toolbox Christian Borgelt and Gil Gonzalez Rodrguez
- ``BisoNet'' Generation using Textual Data Marc Segond and Christian Borgelt
- Dependence Relationships between Gene Ontology Terms based TIGR Gene Product Annotations
- Inhaltsverzeichnis 9 Unsicheres und vages Wissens 291
- Selecting the Links in BisoNets Generated from Document Collections
- A Critique of Inductive Causation Christian Borgelt and Rudolf Kruse
- Feature Weighting and Feature Selection in Fuzzy Clustering Christian Borgelt
- Large Scale Mining of Molecular Fragments with Wildcards
- An Implementation of the FPgrowth Algorithm Christian Borgelt
- Simple Algorithms for Frequent Item Set Mining Christian Borgelt
- Support Computation for Mining Frequent Subgraphs in a Single Graph
- Learning Probabilistic and Possibilistic Networks: Theory and Applications Rudolf Kruse and Christian Borgelt
- Recursion Pruning for the Apriori Algorithm Christian Borgelt
- Data Mining with Possibilistic Graphical Models
- Fuzzy Learning Vector Quantization with Size and Shape Parameters
- Full Perfect Extension Pruning for Frequent Subgraph Mining
- Concepts for Probabilistic and Possibilistic Induction of Decision Trees on Real World Data
- An Empirical Investigation of the K2 Metric Christian Borgelt and Rudolf Kruse
- MODELING AND DIAGNOSIS OF ANALOG CIRCUITS WITH PROBABILISTIC GRAPHICAL MODELS
- Feature Weighting and Feature Selection in Fuzzy Clustering Christian Borgelt
- (Approximate) Frequent Item Set Mining Made Simple with a Split and Merge Algorithm
- Combining Ring Extensions and Canonical Form Pruning
- Possibilistic Graphical Models Christian Borgelt, Jorg Gebhardt, and Rudolf Kruse
- Information Mining Rudolf Kruse and Christian Borgelt
- Item Set Mining Based on Cover Similarity Marc Segond and Christian Borgelt
- Hindawi Publishing Corporation Computational Intelligence and Neuroscience
- "BisoNet" Generation using Textual Data Marc Segond and Christian Borgelt
- Graph Mining: An Overview Christian Borgelt
- Feature Weighting and Feature Selection in Fuzzy Clustering Christian Borgelt
- Accelerating Fuzzy Clustering Christian Borgelt
- Prototype-less Fuzzy Clustering Christian Borgelt
- Abductive Inference with Probabilistic Graphical Models
- Support Computation for Mining Frequent Subgraphs in a Single Graph
- Finding the Number of Fuzzy Clusters by Resampling
- Fixed Parameter Algorithms for the Minimum Weight Triangulation Problem
- Fixed Parameter Algorithms for the Minimum Weight Triangulation Problem
- An Implementation of the FP-growth Algorithm Christian Borgelt
- Keeping Things Simple: Finding Frequent Item Sets by Recursive Elimination
- Minimum Weight Triangulation by Cutting Out Triangles
- Molecular Fragment Mining for Drug Discovery Christian Borgelt1
- Probabilistic Graphical Models for the Diagnosis of Analog Electrical Circuits
- Effects of Irrelevant Attributes in Fuzzy Clustering Christian Doring, Christian Borgelt, and Rudolf Kruse
- Dependence Relationships between Gene Ontology Terms based on TIGR Gene Product Annotations
- IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. XX, NO. Y, MONTH YEAR 1 Learning Possibilistic Graphical Models from Data
- Local Structure Learning in Graphical Models Christian Borgelt and Rudolf Kruse
- On Identifying Tree-Structured Perfect Maps Christian Borgelt
- Learning from Imprecise Data: Possibilistic Graphical Models
- Data Mining with Graphical Models Rudolf Kruse and Christian Borgelt
- An Empirical Investigation of the K2 Metric Christian Borgelt and Rudolf Kruse
- Data Mining with Graphical Models Christian Borgelt
- CHRISTIAN BORGELT AND RUDOLF KRUSE ABDUCTIVE INFERENCE
- Data Mining with Fuzzy Methods: Status and Perspectives
- Possibilistic Networks with Local Structure Christian Borgelt and Rudolf Kruse
- Neue Entwicklungen im Data Mining mit Bayesschen Netzen Rudolf Kruse und Christian Borgelt
- Lernen probabilistischer und possibilistischer Netze aus Daten: Theorie und Anwendung
- F1.2 Inference Methods C Borgelt 1
- Attributauswahlmae fur die Induktion von Entscheidungsbaumen: Ein Uberblick
- Einfuhrung in Datenanalyse und Data Mining mit intelligenten Technologien
- Learning Possibilistic Networks with a Global Evaluation Method Christian Borgelt
- Prototype-based Classification and Clustering
- Subgraph Support in a Single Large Graph Mathias Fiedler and Christian Borgelt
- Discriminative Closed Fragment Mining and Perfect Extensions in MoFa
- Feature Weighting and Feature Selection in Fuzzy Clustering Christian Borgelt
- Data Mining with Fuzzy Methods: Status and Perspectives
- Advanced Pruning Strategies to Speed Up Mining Closed Molecular Fragments #
- Mining Molecular Fragments: Finding Relevant Substructures of Molecules
- (Approximate) Frequent Item Set Mining Made Simple with a Split and Merge Algorithm
- Unsicherheit und Vagheit: Begriffe, Methoden, Forschungsthemen Christian Borgelt und Rudolf Kruse
- MODELING AND DIAGNOSIS OF ANALOG CIRCUITS WITH PROBABILISTIC GRAPHICAL MODELS
- Shape and Size Regularization in Expectation Maximization and Fuzzy Clustering
- Fuzzy Clustering of Quantitative and Qualitative Data
- Finding Discriminative Molecular Fragments Christian Borgelt1
- October 7, 2009 11:25 WSPC/Guidelines ijcga08 Fixed Parameter Algorithms for the
- Fuzzy Frequent Item Set Mining based on Recursive Elimination Xiaomeng Wang, Christian Borgelt and Rudolf Kruse
- A Naive Bayes Style Possibilistic Classifier Christian Borgelt and Jorg Gebhardt
- A Conditional Independence Algorithm for Learning Undirected Graphical Models
- E#cient Maximum Projection of DatabaseInduced Multivariate Possibility Distributions
- Accelerating Fuzzy Clustering Christian Borgelt
- Data Mining with Graphical Models Rudolf Kruse and Christian Borgelt
- MoSS: A Program for Molecular Substructure Mining Christian Borgelt
- Full Perfect Extension Pruning for Frequent Subgraph Mining
- Learning Graphical Models with Hypertree Structure Using a Simulated Annealing Approach
- Operations and Evaluation Measures for Learning Possibilistic Graphical Models
- Item Set Mining Based on Cover Similarity Marc Segond and Christian Borgelt
- Probabilistic Graphical Models for the Diagnosis of Analog Electrical Circuits
- Local Structure Learning in Graphical Models Christian Borgelt and Rudolf Kruse
- Possibilistic Networks: Data Mining Applications Rudolf Kruse and Christian Borgelt
- Induction of Association Rules: Apriori Implementation
- Unsicherheit und Vagheit: Begri#e, Methoden, Forschungsthemen Christian Borgelt und Rudolf Kruse
- Data Mining with Graphical Models Rudolf Kruse and Christian Borgelt
- Full Perfect Extension Pruning for Frequent Graph Mining Christian Borgelt
- Learning Graphical Models by Extending Optimal Spanning Trees
- Graph Mining: Repository vs. Canonical Form Christian Borgelt and Mathias Fiedler
- Finding Closed Frequent Item Sets by Intersecting Transactions
- A Fixed Parameter Algorithm for Minimum Weight Triangulation
- Problems and Prospects in Fuzzy Data Analysis Rudolf Kruse1
- Induction of Association Rules: Apriori Implementation
- Fixed Parameter Algorithms for Minimum Weight Partitions Christian Borgelt
- Data Mining with Graphical Models Christian Borgelt
- Subgraph Support in a Single Large Graph Mathias Fiedler and Christian Borgelt
- Large Scale Mining of Molecular Fragments with Wildcards
- Learning Graphical Models with Hypertree Structure Using a Simulated Annealing Approach
- Combining Ring Extensions and Canonical Form Pruning
- Shape and Size Regularization in Expectation Maximization and Fuzzy Clustering
- Probabilistic Networks and Fuzzy Clustering as Generalizations of Naive Bayes Classifiers
- Notes on the Dynamic Bichromatic All-Nearest-Neighbors Problem Magdalene G. Borgelt
- An Extended Objective Function for Prototype-less Fuzzy Clustering
- The Role of Soft Computing in Intelligent Data Analysis (Invited Paper)
- Operations and Evaluation Measures for Learning Possibilistic Graphical Models
- Fuzzy Subspace Clustering Christian Borgelt
- Speeding Up Fuzzy Clustering with Neural Network Techniques
- On Canonical Forms for Frequent Graph Mining Christian Borgelt
- Fixed Parameter Algorithms for the Minimum Weight Triangulation Problem
- Using Fuzzy Clustering to Improve Naive Bayes Classifiers and Probabilistic Networks
- Prototypebased Classification and Clustering
- Fuzzy Clustering of Quantitative and Qualitative Data
- Experiments in Document Clustering using Cluster Specific Term Weights
- Experiments in Term Weighting and Keyword Extraction in Document Clustering
- Learning Graphical Models by Extending Optimal Spanning Trees
- Naive Bayes Classifiers Using Neuro-Fuzzy Learning1
- Fuzzy Data Analysis: Challenges and Perspectives Rudolf Kruse, Christian Borgelt, and Detlef Nauck
- Finding Ensembles of Neurons in Spike Trains by Non-linear Mapping and Statistical Testing
- Frequent Route Based Continuous Moving Object Location-and Density Prediction on Road Networks
- Mining Faulttolerant Item Sets using Subset Size Occurrence Distributions
- Finding Ensembles of Neurons in Spike Trains by Nonlinear Mapping and Statistical Testing
- Mining Fault-tolerant Item Sets using Subset Size Occurrence Distributions
