Data structures and algorithms 3: multi-dimensional searching and computational geometry
Data structures and algorithms 3: multi-dimensional searching and computational geometry
Communications of the ACM
Computational geometry: an introduction
Computational geometry: an introduction
Maximizing the predictive value of production rules
Artificial Intelligence
Toward efficient agnostic learning
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
A Further Comparison of Splitting Rules for Decision-Tree Induction
Machine Learning
C4.5: programs for machine learning
C4.5: programs for machine learning
Learning in the presence of malicious errors
SIAM Journal on Computing
Decision theoretic generalizations of the PAC model for neural net and other learning applications
Information and Computation
Efficient noise-tolerant learning from statistical queries
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
Statistical queries and faulty PAC oracles
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
Machine Learning
Computing the rectangle discrepancy
SCG '94 Proceedings of the tenth annual symposium on Computational geometry
Concept learning with geometric hypotheses
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
More or less efficient agnostic learning of convex polygons
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
General and Efficient Multisplitting of Numerical Attributes
Machine Learning
RainForest—A Framework for Fast Decision Tree Construction of Large Datasets
Data Mining and Knowledge Discovery
Discretization: An Enabling Technique
Data Mining and Knowledge Discovery
Parallel Incremental 2D-Discretization on Dynamic Datasets
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
Optimized Substructure Discovery for Semi-structured Data
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
RainForest - A Framework for Fast Decision Tree Construction of Large Datasets
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
A Fast Algorithm for Discovering Optimal String Patterns in Large Text Databases
ALT '98 Proceedings of the 9th International Conference on Algorithmic Learning Theory
Efficient Multisplitting Revisited: Optima-Preserving Elimination of Partition Candidates
Data Mining and Knowledge Discovery
Computers and Operations Research
On the Computational Complexity of Optimal Multisplitting
Fundamenta Informaticae - Intelligent Systems
Fuzzy classification systems based on fuzzy information gain measures
Expert Systems with Applications: An International Journal
Correlation maximisation-based discretisation for supervised classification
International Journal of Business Intelligence and Data Mining
On the Computational Complexity of Optimal Multisplitting
Fundamenta Informaticae - Intelligent Systems
From Optimal Hyperplanes to Optimal Decision Trees
Fundamenta Informaticae
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We exhibit efficient algorithms for agnostic PAC-learning with rectangles, unions of two rectangles, and unions of k intervals as hypotheses. These hypothesis classes are of some interest from the point of view of applied machine learning, because empirical studies show that hypotheses of this simple type (in just one or two of the attributes) provide good prediction rules for various real-world classification problems. In addition, optimal hypotheses of this type may provide valuable heuristic insight into the structure of a real world classification problem.The algorithms that are introduced in this paper make it feasible to compute optimal hypotheses of this type for a training set of several hundred examples. We also exhibit an approximation algorithm that can compute nearly optimal hypotheses for much larger datasets.