Machine Learning
A simple, fast, and effective rule learner
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Boosting the margin: A new explanation for the effectiveness of voting methods
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Rule-based machine learning methods for functional prediction
Journal of Artificial Intelligence Research
Data-intensive analytics for predictive modeling
IBM Journal of Research and Development
A Data Mining Approach for Retailing Bank Customer Attrition Analysis
Applied Intelligence
A general framework for accurate and fast regression by data summarization in random decision trees
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Solving Regression by Learning an Ensemble of Decision Rules
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Using Ensemble-Based Reasoning to Help Experts in Melanoma Diagnosis
Proceedings of the 2008 conference on Artificial Intelligence Research and Development: Proceedings of the 11th International Conference of the Catalan Association for Artificial Intelligence
Elgasir: an algorithm for creating fuzzy regression trees
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
Learning to combine discriminative classifiers: confidence based
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Rule-based data mining for yield improvement in semiconductor manufacturing
Applied Intelligence
Predictive rule discovery from electronic health records
Proceedings of the 1st ACM International Health Informatics Symposium
Rule-Based prediction of rare extreme values
DS'06 Proceedings of the 9th international conference on Discovery Science
Novel ensemble methods for regression via classification problems
Expert Systems with Applications: An International Journal
Support vector regression based on data shifting
Neurocomputing
Ensemble methods for prediction of parkinson disease
IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning
Multi-target regression with rule ensembles
The Journal of Machine Learning Research
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We describe a lightweight learning method that induces an ensemble of decision-rule solutions for regression problems. Instead of direct prediction of a continuous output variable, the method discretizes the variable by k-means clustering and solves the resultant classification problem. Predictions on new examples are made by averaging the mean values of classes with votes that are close in number to the most likely class. We provide experimental evidence that this indirect approach can often yield strong results for many applications, generally outperforming direct approaches such as regression trees and rivaling bagged regression trees.