Instance-Based Learning Algorithms
Machine Learning
What Makes a Problem Hard for a Genetic Algorithm? Some Anomalous Results and Their Explanation
Machine Learning - Special issue on genetic algorithms
Editing for the k-nearest neighbors rule by a genetic algorithm
Pattern Recognition Letters - Special issue on genetic algorithms
Reduction Techniques for Instance-BasedLearning Algorithms
Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Design of an optimal nearest neighbor classifier using an intelligent genetic algorithm
Pattern Recognition Letters
Machine Learning
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Using evolutionary algorithms as instance selection for data reduction in KDD: an experimental study
IEEE Transactions on Evolutionary Computation
The reduced nearest neighbor rule (Corresp.)
IEEE Transactions on Information Theory
An algorithm for a selective nearest neighbor decision rule (Corresp.)
IEEE Transactions on Information Theory
A memetic algorithm for evolutionary prototype selection: A scaling up approach
Pattern Recognition
Making CN2-SD subgroup discovery algorithm scalable to large size data sets using instance selection
Expert Systems with Applications: An International Journal
A divide-and-conquer recursive approach for scaling up instance selection algorithms
Data Mining and Knowledge Discovery
Evolutionary undersampling for classification with imbalanced datasets: Proposals and taxonomy
Evolutionary Computation
A review of instance selection methods
Artificial Intelligence Review
Parallel distributed implementation of genetics-based machine learning for fuzzy classifier design
SEAL'10 Proceedings of the 8th international conference on Simulated evolution and learning
Information Sciences: an International Journal
A comparison of two strategies for scaling up instance selection in huge datasets
CAEPIA'11 Proceedings of the 14th international conference on Advances in artificial intelligence: spanish association for artificial intelligence
Expert Systems with Applications: An International Journal
Incorporating knowledge in evolutionary prototype selection
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
Editorial: Large scale instance selection by means of federal instance selection
Data & Knowledge Engineering
A scalable approach to simultaneous evolutionary instance and feature selection
Information Sciences: an International Journal
On the use of meta-learning for instance selection: An architecture and an experimental study
Information Sciences: an International Journal
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Evolutionary algorithms has been recently used for prototype selection showing good results. An important problem that we can find is the scaling up problem that appears evaluating the Evolutionary Prototype Selection algorithms in large size data sets. In this paper, we offer a proposal to solve the drawbacks introduced by the evaluation of large size data sets using evolutionary prototype selection algorithms. In order to do this we have proposed a combination of stratified strategy and CHC as representative evolutionary algorithm model. This study includes a comparison between our proposal and other non-evolutionary prototype selection algorithms combined with the stratified strategy. The results show that stratified evolutionary prototype selection consistently outperforms the non-evolutionary ones, the main advantages being: better instance reduction rates, higher classification accuracy and reduction in resources consumption.