Information retrieval based on context distance and morphology
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Machine Learning
Local overfitting control via leverages
Neural Computation
An introduction to variable and feature selection
The Journal of Machine Learning Research
Dimensionality reduction via sparse support vector machines
The Journal of Machine Learning Research
C4.5 competence map: a phase transition-inspired approach
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Variable selection and ranking for analyzing automobile traffic accident data
Proceedings of the 2005 ACM symposium on Applied computing
Feature Selection via Coalitional Game Theory
Neural Computation
Integrating support vector machines and neural networks
Neural Networks
Consensus unsupervised feature ranking from multiple views
Pattern Recognition Letters
Unsupervised feature selection for principal components analysis
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III
An improved approximation algorithm for the column subset selection problem
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
Feature Selection in Marketing Applications
ADMA '09 Proceedings of the 5th International Conference on Advanced Data Mining and Applications
A decision rule-based method for feature selection in predictive data mining
Expert Systems with Applications: An International Journal
Computer Methods and Programs in Biomedicine
Improved variable and value ranking techniques for mining categorical traffic accident data
Expert Systems with Applications: An International Journal
Feature Selection with Ensembles, Artificial Variables, and Redundancy Elimination
The Journal of Machine Learning Research
Applying cost sensitive feature selection in an electric database
ISMIS'08 Proceedings of the 17th international conference on Foundations of intelligent systems
On the relevance of linear discriminative features
Information Sciences: an International Journal
Computational Statistics & Data Analysis
Applying electromagnetism-like mechanism for feature selection
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Power system database feature selection using a relaxed perceptron paradigm
MICAI'06 Proceedings of the 5th Mexican international conference on Artificial Intelligence
ICANN'05 Proceedings of the 15th international conference on Artificial Neural Networks: biological Inspirations - Volume Part I
Analysis of feature rankings for classification
IDA'05 Proceedings of the 6th international conference on Advances in Intelligent Data Analysis
An optimization approach for feature selection in an electric billing database
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part IV
Learning the reasons why groups of consumers prefer some food products
ICDM'06 Proceedings of the 6th Industrial Conference on Data Mining conference on Advances in Data Mining: applications in Medicine, Web Mining, Marketing, Image and Signal Mining
Evolutionary search of optimal features
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
Blind Kriging: Implementation and performance analysis
Advances in Engineering Software
Sensor selection to support practical use of health-monitoring smart environments
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Using random subspace method for prediction and variable importance assessment in linear regression
Computational Statistics & Data Analysis
Advances in Artificial Neural Systems
A survey on feature selection methods
Computers and Electrical Engineering
A scatter method for data and variable importance evaluation
Integrated Computer-Aided Engineering
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We describe a feature selection method that can be applied directly to models that are linear with respect to their parameters, and indirectly to others. It is independent of the target machine. It is closely related to classical statistical hypothesis tests, but it is more intuitive, hence more suitable for use by engineers who are not statistics experts. Furthermore, some assumptions of classical tests are relaxed. The method has been used successfully in a number of applications that are briefly described.