Numerical recipes in C: the art of scientific computing
Numerical recipes in C: the art of scientific computing
Original Contribution: Stacked generalization
Neural Networks
C4.5: programs for machine learning
C4.5: programs for machine learning
Essentials of artificial intelligence
Essentials of artificial intelligence
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Machine Learning
Wrappers for performance enhancement and oblivious decision graphs
Wrappers for performance enhancement and oblivious decision graphs
Theories for mutagenicity: a study in first-order and feature-based induction
Artificial Intelligence - Special volume on empirical methods
Database management systems
Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
Combining labeled and unlabeled data with co-training
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Top-down induction of first-order logical decision trees
Artificial Intelligence
Category learning through multimodality sensing
Neural Computation
MetaCost: a general method for making classifiers cost-sensitive
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
MultiBoosting: A Technique for Combining Boosting and Wagging
Machine Learning
Parallel data mining for association rules on shared memory systems
Knowledge and Information Systems
Distributed web log mining using maximal large item sets
Knowledge and Information Systems
Parallel and sequential algorithms for data mining using inductive logic
Knowledge and Information Systems
Distributed clustering using collective principal component analysis
Knowledge and Information Systems
Inductive Logic Programming: Techniques and Applications
Inductive Logic Programming: Techniques and Applications
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Data Mining and Knowledge Discovery
Scaling Up Inductive Logic Programming by Learning from Interpretations
Data Mining and Knowledge Discovery
RainForest—A Framework for Fast Decision Tree Construction of Large Datasets
Data Mining and Knowledge Discovery
Efficient Mining of Association Rules in Distributed Databases
IEEE Transactions on Knowledge and Data Engineering
Machine Learning
Distributed mining of classification rules
Knowledge and Information Systems
Database Mining: A Performance Perspective
IEEE Transactions on Knowledge and Data Engineering
Synthesizing High-Frequency Rules from Different Data Sources
IEEE Transactions on Knowledge and Data Engineering
ECML '93 Proceedings of the European Conference on Machine Learning
Learning Probabilistic Models of Relational Structure
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
ALT '95 Proceedings of the 6th International Conference on Algorithmic Learning Theory
Adaptive duplicate detection using learnable string similarity measures
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Aggregation-based feature invention and relational concept classes
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Learning relational probability trees
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Multi-relational data mining: an introduction
ACM SIGKDD Explorations Newsletter
Active learning with multiple views
Active learning with multiple views
CrossMine: Efficient Classification Across Multiple Database Relations
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
On Leveraging User Access Patterns for Topic Specific Crawling
Data Mining and Knowledge Discovery
Collective Mining of Bayesian Networks from Distributed Heterogeneous Data
Knowledge and Information Systems
Learning from imbalanced data sets with boosting and data generation: the DataBoost-IM approach
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
Multistrategy Ensemble Learning: Reducing Error by Combining Ensemble Learning Techniques
IEEE Transactions on Knowledge and Data Engineering
Database classification for multi-database mining
Information Systems
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Mining relational databases with multi-view learning
MRDM '05 Proceedings of the 4th international workshop on Multi-relational mining
Online feature selection for pixel classification
ICML '05 Proceedings of the 22nd international conference on Machine learning
Accurate Prediction of Protein Disordered Regions by Mining Protein Structure Data
Data Mining and Knowledge Discovery
Mining relational data through correlation-based multiple view validation
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Adaptive Blocking: Learning to Scale Up Record Linkage
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
Database Systems: The Complete Book
Database Systems: The Complete Book
Discriminative probabilistic models for relational data
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Estimating continuous distributions in Bayesian classifiers
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Regression on evolving multi-relational data streams
Proceedings of the 2011 Joint EDBT/ICDT Ph.D. Workshop
Boosting tuple propagation in multi-relational classification
Proceedings of the 15th Symposium on International Database Engineering & Applications
Privacy leakage in multi-relational learning via unwanted classification models
Proceedings of the 2011 Conference of the Center for Advanced Studies on Collaborative Research
Transductive relational classification in the co-training paradigm
MLDM'12 Proceedings of the 8th international conference on Machine Learning and Data Mining in Pattern Recognition
Dimensionality reduction in data summarization approach to learning relational data
ACIIDS'13 Proceedings of the 5th Asian conference on Intelligent Information and Database Systems - Volume Part I
Reducing the size of databases for multirelational classification: a subgraph-based approach
Journal of Intelligent Information Systems
Learning in the presence of large fluctuations: a study of aggregation and correlation
NFMCP'12 Proceedings of the First international conference on New Frontiers in Mining Complex Patterns
Genetic algorithm-based optimized association rule mining for multi-relational data
Intelligent Data Analysis
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Multirelational classification aims at discovering useful patterns across multiple inter-connected tables (relations) in a relational database. Many traditional learning techniques, however, assume a single table or a flat file as input (the so-called propositional algorithms). Existing multirelational classification approaches either “upgrade” mature propositional learning methods to deal with relational presentation or extensively “flatten” multiple tables into a single flat file, which is then solved by propositional algorithms. This article reports a multiple view strategy—where neither “upgrading” nor “flattening” is required—for mining in relational databases. Our approach learns from multiple views (feature set) of a relational databases, and then integrates the information acquired by individual view learners to construct a final model. Our empirical studies show that the method compares well in comparison with the classifiers induced by the majority of multirelational mining systems, in terms of accuracy obtained and running time needed. The paper explores the implications of this finding for multirelational research and applications. In addition, the method has practical significance: it is appropriate for directly mining many real-world databases.