Information Processing Letters
Inferring decision trees using the minimum description length principle
Information and Computation
C4.5: programs for machine learning
C4.5: programs for machine learning
Machine Learning
Learning Logical Definitions from Relations
Machine Learning
Machine Learning
Overfitting and undercomputing in machine learning
ACM Computing Surveys (CSUR)
An Exact Probability Metric for Decision Tree Splitting and Stopping
Machine Learning
Separate-and-Conquer Rule Learning
Artificial Intelligence Review
Multiple Comparisons in Induction Algorithms
Machine Learning
Mining high-speed data streams
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
The Role of Occam‘s Razor in Knowledge Discovery
Data Mining and Knowledge Discovery
A Unified Framework for Evaluation Metrics in Classification Using Decision Trees
EMCL '01 Proceedings of the 12th European Conference on Machine Learning
Texture Based Look-Ahead for Decision-Tree Induction
ICAPR '01 Proceedings of the Second International Conference on Advances in Pattern Recognition
Learning with Globally Predictive Tests
DS '98 Proceedings of the First International Conference on Discovery Science
Worst-Case Analysis of Rule Discovery
DS '01 Proceedings of the 4th International Conference on Discovery Science
Some Elements of Machine Learning (Extended Abstract)
ILP '99 Proceedings of the 9th International Workshop on Inductive Logic Programming
Knowledge evaluation: statistical evaluations
Handbook of data mining and knowledge discovery
Handbook of data mining and knowledge discovery
Simplifying decision trees: A survey
The Knowledge Engineering Review
An intelligent system for customer targeting: a data mining approach
Decision Support Systems
Anytime Learning of Decision Trees
The Journal of Machine Learning Research
Discovering Significant Patterns
Machine Learning
Mining optimal decision trees from itemset lattices
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Variable step search algorithm for feedforward networks
Neurocomputing
OPUS: an efficient admissible algorithm for unordered search
Journal of Artificial Intelligence Research
Decision tree grafting from the all-tests-but-one partition
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Process-oriented estimation of generalization error
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Support feature machine for DNA microarray data
RSCTC'10 Proceedings of the 7th international conference on Rough sets and current trends in computing
Scaling up: distributed machine learning with cooperation
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Effectiveness of document representation for classification
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
A study of applying dimensionality reduction to restrict the size of a hypothesis space
ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
Comparison of metaheuristic strategies for peakbin selection in proteomic mass spectrometry data
Information Sciences: an International Journal
Parallel data mining revisited. better, not faster
IDA'12 Proceedings of the 11th international conference on Advances in Intelligent Data Analysis
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When learning classifiers, more extensive search for rules is shown to lead to lower predictive accuracy on many of the leal-world domains investigated. This counter-intuitive re suit is particularly relevant to recent system the search methods that use risk-free pruning to achieve the same outcome as exhaustive search. We propose an iterated search method that commences with greedy search extending its scope at each Iteration until a stopping criterion is satisfied. This layered search is often found to produce theories that are more accurate than those obtained with either greedy search or moderately, extensive beam search.