Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Learning Boolean concepts in the presence of many irrelevant features
Artificial Intelligence
An introduction to genetic algorithms
An introduction to genetic algorithms
Machine Learning
Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Boosting the margin: A new explanation for the effectiveness of voting methods
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Connectionist theory refinement: genetically searching the space of network topologies
Journal of Artificial Intelligence Research
An empirical evaluation of bagging and boosting
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
A streaming ensemble algorithm (SEA) for large-scale classification
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Ensemble Feature Selection Based on Contextual Merit and Correlation Heuristics
ADBIS '01 Proceedings of the 5th East European Conference on Advances in Databases and Information Systems
Ensemble Feature Selection Based on the Contextual Merit
DaWaK '01 Proceedings of the Third International Conference on Data Warehousing and Knowledge Discovery
Feature Selection for Ensembles of Simple Bayesian Classifiers
ISMIS '02 Proceedings of the 13th International Symposium on Foundations of Intelligent Systems
Correlation-Based and Contextual Merit-Based Ensemble Feature Selection
IDA '01 Proceedings of the 4th International Conference on Advances in Intelligent Data Analysis
Feature selection in data mining
Data mining
Feature Selection for Ensembles: A Hierarchical Multi-Objective Genetic Algorithm Approach
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Genetic programming in classifying large-scale data: an ensemble method
Information Sciences: an International Journal - Special issue: Soft computing data mining
Ensemble selection from libraries of models
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Non-strict heterogeneous Stacking
Pattern Recognition Letters
Nonlinear Boosting Projections for Ensemble Construction
The Journal of Machine Learning Research
A hybrid genetic algorithm for feature selection wrapper based on mutual information
Pattern Recognition Letters
Evolutionary model selection in unsupervised learning
Intelligent Data Analysis
Adaptive boosting techniques in heterogeneous and spatial databases
Intelligent Data Analysis
The random electrode selection ensemble for EEG signal classification
Pattern Recognition
Genetic algorithm-based feature set partitioning for classification problems
Pattern Recognition
The random electrode selection ensemble for EEG signal classification
Pattern Recognition
Genetic algorithm-based feature set partitioning for classification problems
Pattern Recognition
Mining manufacturing data using genetic algorithm-based feature set decomposition
International Journal of Intelligent Systems Technologies and Applications
Feature Extraction for Dynamic Integration of Classifiers
Fundamenta Informaticae
The combination of multiple classifiers using an evidential reasoning approach
Artificial Intelligence
Combining Answers of Sub-classifiers in the Bagging-Feature Ensembles
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part I
Combining Classifiers through Triplet-Based Belief Functions
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
Boosting and measuring the performance of ensembles for a successful database marketing
Expert Systems with Applications: An International Journal
Resampling-based selective clustering ensembles
Pattern Recognition Letters
Engineering Applications of Artificial Intelligence
Comparative study of fuzzy methods for response integration in ensemble neural networks
International Journal of Advanced Intelligence Paradigms
A New Approach to Improving ICA-Based Models for the Classification of Microarray Data
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III
MCS '09 Proceedings of the 8th International Workshop on Multiple Classifier Systems
Computational Statistics & Data Analysis
On Feature Selection, Bias-Variance, and Bagging
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II
Constraint projections for ensemble learning
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Microarray data classification based on ensemble independent component selection
Computers in Biology and Medicine
Sequential genetic search for ensemble feature selection
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Computer Methods and Programs in Biomedicine
Random subspaces of the instance and principal component spaces for ensembles
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Artificial Intelligence Review
Bagging Constraint Score for feature selection with pairwise constraints
Pattern Recognition
Expert Systems with Applications: An International Journal
An improved random subspace method and its application to EEG signal classification
MCS'07 Proceedings of the 7th international conference on Multiple classifier systems
Exploiting diversity in ensembles: improving the performance on unbalanced datasets
MCS'07 Proceedings of the 7th international conference on Multiple classifier systems
Negative correlation learning and the ambiguity family of ensemble methods
MCS'03 Proceedings of the 4th international conference on Multiple classifier systems
An approach for selective ensemble feature selection based on rough set theory
RSKT'07 Proceedings of the 2nd international conference on Rough sets and knowledge technology
Selecting features from multiple feature sets for SVM committee-based screening of human larynx
Expert Systems with Applications: An International Journal
A dynamic classifier ensemble selection approach for noise data
Information Sciences: an International Journal
Artificial Intelligence in Medicine
Bootstrap feature selection for ensemble classifiers
ICDM'10 Proceedings of the 10th industrial conference on Advances in data mining: applications and theoretical aspects
A class-specific ensemble feature selection approach for classification problems
Proceedings of the 48th Annual Southeast Regional Conference
Search strategies for ensemble feature selection in medical diagnostics
CBMS'03 Proceedings of the 16th IEEE conference on Computer-based medical systems
The design of evolutionary multiple classifier system for the classification of microarray data
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part III
An ensemble of filters and classifiers for microarray data classification
Pattern Recognition
A multilevel information fusion approach for visual quality inspection
Information Fusion
GA SVM wrapper ensemble for keystroke dynamics authentication
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
An evolutionary and attribute-oriented ensemble classifier
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part II
Multi-objective genetic algorithms to create ensemble of classifiers
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Ensemble algorithms for feature selection
Proceedings of the First international conference on Deterministic and Statistical Methods in Machine Learning
New feature splitting criteria for co-training using genetic algorithm optimization
MCS'10 Proceedings of the 9th international conference on Multiple Classifier Systems
Off-line cursive script recognition: current advances, comparisons and remaining problems
Artificial Intelligence Review
ReinSel: A class-based mechanism for feature selection in ensemble of classifiers
Applied Soft Computing
Feature Extraction for Dynamic Integration of Classifiers
Fundamenta Informaticae
RSGALS-SVM: random subspace method applied to a LS-SVM ensemble optimized by genetic algorithm
IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning
Ensemble approaches for regression: A survey
ACM Computing Surveys (CSUR)
Random subspace method and genetic algorithm applied to a LS-SVM ensemble
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part II
Bi-objective genetic algorithm for feature selection in ensemble systems
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part I
Exploiting unlabeled data to enhance ensemble diversity
Data Mining and Knowledge Discovery
A Novel Emotion Recognition Method Based on Ensemble Learning and Rough Set Theory
International Journal of Cognitive Informatics and Natural Intelligence
Co-regularized ensemble for feature selection
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Filter-based optimization techniques for selection of feature subsets in ensemble systems
Expert Systems with Applications: An International Journal
Combining multiple predictive models using genetic algorithms
Intelligent Data Analysis - Combined Learning Methods and Mining Complex Data
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The traditional motivation behind feature selection algorithms is to find the best subset of features for a task using one particular learning algonthm. Given the recent success of ensembles, however, we investigate the notion of ensemble feature selection in this paper. This task is harder than traditional feature selection in that one not only needs to find features germane to the learning task and learning algorithm, but one also needs to find a set of feature subsets that will promote disagreement among the ensemble's classifiers. In this paper, we present an ensemble feature selection approach that is based on genetic algorithms. Our algorithm shows improved performance over the popular and powerful ensemble approaches of AdaBoost and Bagging and demonstrates the utility of ensemble feature selection.