Instance-Based Learning Algorithms
Machine Learning
C4.5: programs for machine learning
C4.5: programs for machine learning
Feature Selection: Evaluation, Application, and Small Sample Performance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
The Random Subspace Method for Constructing Decision Forests
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature selection for ensembles
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
Feature selection in unsupervised learning via evolutionary search
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine Learning
Diversity versus Quality in Classification Ensembles Based on Feature Selection
ECML '00 Proceedings of the 11th European Conference on Machine Learning
Machine learning in DNA microarray analysis for cancer classification
APBC '03 Proceedings of the First Asia-Pacific bioinformatics conference on Bioinformatics 2003 - Volume 19
Knowledge discovery in databases: 10 years after
ACM SIGKDD Explorations Newsletter
An introduction to variable and feature selection
The Journal of Machine Learning Research
An extensive empirical study of feature selection metrics for text classification
The Journal of Machine Learning Research
Toward Integrating Feature Selection Algorithms for Classification and Clustering
IEEE Transactions on Knowledge and Data Engineering
Introduction to Data Mining, (First Edition)
Introduction to Data Mining, (First Edition)
Consistent Feature Selection for Pattern Recognition in Polynomial Time
The Journal of Machine Learning Research
Empirical Study of Feature Selection Methods in Classification
HIS '08 Proceedings of the 2008 8th International Conference on Hybrid Intelligent Systems
A Class-Based Feature Selection Method for Ensemble Systems
HIS '08 Proceedings of the 2008 8th International Conference on Hybrid Intelligent Systems
Ensembles as a sequence of classifiers
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Search strategies for ensemble feature selection in medical diagnostics
CBMS'03 Proceedings of the 16th IEEE conference on Computer-based medical systems
A class centric feature and classifier ensemble selection approach for music genre classification
SSPR'12/SPR'12 Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
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Due to substantial increases in data acquisition and storage, data pre-processing techniques such as feature selection have become increasingly popular in classification tasks. This research proposes a new feature selection algorithm, Class-specific Ensemble Feature Selection (CEFS), which finds class-specific subsets of features optimal to each available classification in the dataset. Each subset is then combined with a classifier to create an ensemble feature selection model which is further used to predict unseen instances. CEFS attempts to provide the diversity and base classifier disagreement sought after in effective ensemble models by providing highly useful, yet highly exclusive feature subsets. Also, the use of a wrapper method gives each subset the chance to perform optimally under the respective base classifier. Preliminary experiments implementing this innovative approach suggest potential improvements of more than 10% over existing methods.