Instance-Based Learning Algorithms
Machine Learning
C4.5: programs for machine learning
C4.5: programs for machine learning
Trading Accuracy for Simplicity in Decision Trees
Machine Learning
Editing for the k-nearest neighbors rule by a genetic algorithm
Pattern Recognition Letters - Special issue on genetic algorithms
Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
A Comparative Analysis of Methods for Pruning Decision Trees
IEEE Transactions on Pattern Analysis and Machine Intelligence
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Reduction Techniques for Instance-BasedLearning Algorithms
Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
On Issues of Instance Selection
Data Mining and Knowledge Discovery
Design of an optimal nearest neighbor classifier using an intelligent genetic algorithm
Pattern Recognition Letters
When Does Overfitting Decrease Prediction Accuracy in Induced Decision Trees and Rule Sets?
EWSL '91 Proceedings of the European Working Session on Machine Learning
The Effects of Training Set Size on Decision Tree Complexity
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Instance Pruning as an Information Preserving Problem
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
AIME '01 Proceedings of the 8th Conference on AI in Medicine in Europe: Artificial Intelligence Medicine
Error-Based Pruning of Decision Trees Grown on Very Large Data Sets Can Work!
ICTAI '02 Proceedings of the 14th IEEE International Conference on Tools with Artificial Intelligence
A Compact and Accurate Model for Classification
IEEE Transactions on Knowledge and Data Engineering
Simplifying decision trees: A survey
The Knowledge Engineering Review
Evaluation of decision trees: a multi-criteria approach
Computers and Operations Research
Stratification for scaling up evolutionary prototype selection
Pattern Recognition Letters
Learning Vector Quantization with Training Data Selection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Data set Editing by Ordered Projection
Intelligent Data Analysis
Using evolutionary algorithms as instance selection for data reduction in KDD: an experimental study
IEEE Transactions on Evolutionary Computation
Medical diagnosis with C4.5 rule preceded by artificial neural network ensemble
IEEE Transactions on Information Technology in Biomedicine
The condensed nearest neighbor rule (Corresp.)
IEEE Transactions on Information Theory
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
Making CN2-SD subgroup discovery algorithm scalable to large size data sets using instance selection
Expert Systems with Applications: An International Journal
Explaining instance classifications with interactions of subsets of feature values
Data & Knowledge Engineering
An optimization of ReliefF for classification in large datasets
Data & Knowledge Engineering
Evolutionary undersampling for classification with imbalanced datasets: Proposals and taxonomy
Evolutionary Computation
Information Sciences: an International Journal
A survey on the application of genetic programming to classification
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Subset selection from multi-experiment data sets with application to milk fatty acid profiles
Computers and Electronics in Agriculture
Evolutionary selection of hyperrectangles in nested generalized exemplar learning
Applied Soft Computing
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Editorial: Large scale instance selection by means of federal instance selection
Data & Knowledge Engineering
Extraction of fuzzy rules from fuzzy decision trees: An axiomatic fuzzy sets (AFS) approach
Data & Knowledge Engineering
An interpretable classification rule mining algorithm
Information Sciences: an International Journal
Information Sciences: an International Journal
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The generation of predictive models is a frequent task in data mining with the objective of generating highly precise and interpretable models. The data reduction is an interesting preprocessing approach that can allow us to obtain predictive models with these characteristics in large size data sets. In this paper, we analyze the rule classification model based on decision trees using a training selected set via evolutionary stratified instance selection. This method faces the scaling problem that appears in the evaluation of large size data sets, and the trade off interpretability-precision of the generated models.