Communications of the ACM - Special issue on parallelism
Instance-Based Learning Algorithms
Machine Learning
A Nearest Hyperrectangle Learning Method
Machine Learning
C4.5: programs for machine learning
C4.5: programs for machine learning
A hybrid nearest-neighbor and nearest-hyperrectangle algorithm
ECML-94 Proceedings of the European conference on machine learning on Machine Learning
Machine Learning
Rule Induction with CN2: Some Recent Improvements
EWSL '91 Proceedings of the European Working Session on Machine Learning
Temporal sequence learning and data reduction for anomaly detection
ACM Transactions on Information and System Security (TISSEC)
Reduction Techniques for Instance-BasedLearning Algorithms
Machine Learning
Understanding the Crucial Role of AttributeInteraction in Data Mining
Artificial Intelligence Review
Advances in Instance Selection for Instance-Based Learning Algorithms
Data Mining and Knowledge Discovery
Rule-Induction and Case-Based Reasoning: Hybrid Architectures Appear Advantageous
IEEE Transactions on Knowledge and Data Engineering
A Language-Based Similarity Measure
EMCL '01 Proceedings of the 12th European Conference on Machine Learning
Speeding up Recommender Systems with Meta-prototypes
SBIA '02 Proceedings of the 16th Brazilian Symposium on Artificial Intelligence: Advances in Artificial Intelligence
Intelligent Rollups in Multidimensional OLAP Data
Proceedings of the 27th International Conference on Very Large Data Bases
Identifying and Eliminating Irrelevant Instances Using Information Theory
AI '00 Proceedings of the 13th Biennial Conference of the Canadian Society on Computational Studies of Intelligence: Advances in Artificial Intelligence
Keep It Simple: A Case-Base Maintenance Policy Based on Clustering and Information Theory
AI '00 Proceedings of the 13th Biennial Conference of the Canadian Society on Computational Studies of Intelligence: Advances in Artificial Intelligence
Learning Logic Programs with Neural Networks
ILP '01 Proceedings of the 11th International Conference on Inductive Logic Programming
Possibilistic instance-based learning
Artificial Intelligence - Special issue: Fuzzy set and possibility theory-based methods in artificial intelligence
An efficient data structure for decision rules discovery
Proceedings of the 2003 ACM symposium on Applied computing
Combining Feature Reduction and Case Selection in Building CBR Classifiers
IEEE Transactions on Knowledge and Data Engineering
Nearest Neighbors by Neighborhood Counting
IEEE Transactions on Pattern Analysis and Machine Intelligence
Weighted Instance Typicality Search (WITS): A nearest neighbor data reduction algorithm
Intelligent Data Analysis
Prototype induction and attribute selection via evolutionary algorithms
Intelligent Data Analysis
Mining competent case bases for case-based reasoning
Artificial Intelligence
Efficient instance-based learning on data streams
Intelligent Data Analysis
A General Similarity Framework for Horn Clause Logic
Fundamenta Informaticae
Tractable induction and classification in first order logic via stochastic matching
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Improved heterogeneous distance functions
Journal of Artificial Intelligence Research
Remembering to add: competence-preserving case-addition policies for case-base maintenance
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Multistrategy learning: a case study
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
A rule-based method for customer churn prediction in telecommunication services
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part I
Automatically evolving rule induction algorithms
ECML'06 Proceedings of the 17th European conference on Machine Learning
An approach to reduce the cost of evaluation in evolutionary learning
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
A General Similarity Framework for Horn Clause Logic
Fundamenta Informaticae
Machine Learning-Based Runtime Scheduler for Mobile Offloading Framework
UCC '13 Proceedings of the 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing
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This paper presents a new approach to inductive learning that combines aspects of instancebased learning and rule induction in a single simple algorithm. The RISE system searches for rules in a specific-to-general fashion, starting with one rule per training example, and avoids some of the difficulties of separate-and-eonquer approaches by evaluating each proposed induction step globally, i e, through an efficient procedure that is equivalent to checking the accuracy of the rule set as a whole on every training example. Classification is performed using a best-match strategy, and reduces to nearest-neighbor if all generalizations of instances were rejected. An extensive empirical study shows that RISE consistently achieves higher accuracies than state-of-the-art representatives of its "parent" paradigms (PEBLS and CN2), and also outperforms a decision-tree learner (C4 5) in 13 out of 15 test domains (in 10 with 95% confidence).