Statistical Pattern Recognition: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Incremental Learning with Respect to New Incoming Input Attributes
Neural Processing Letters
Feature selection with neural networks
Pattern Recognition Letters
Co-operative Evolution of a Neural Classifier and Feature Subset
SEAL'98 Selected papers from the Second Asia-Pacific Conference on Simulated Evolution and Learning on Simulated Evolution and Learning
SOAP: Efficient Feature Selection of Numeric Attributes
IBERAMIA 2002 Proceedings of the 8th Ibero-American Conference on AI: Advances in Artificial Intelligence
A Function-Based Classifier Learning Scheme Using Genetic Programming
PAKDD '02 Proceedings of the 6th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
On learning to predict web traffic
Decision Support Systems - Special issue: Web data mining
Binary and multicategory classification accuracy of the LSA machine
ICCMSE '03 Proceedings of the international conference on Computational methods in sciences and engineering
Semantics-Preserving Dimensionality Reduction: Rough and Fuzzy-Rough-Based Approaches
IEEE Transactions on Knowledge and Data Engineering
Selecting salient features for classification based on neural network committees
Pattern Recognition Letters
On fuzzy-rough sets approach to feature selection
Pattern Recognition Letters
Learning Vector Quantization with Training Data Selection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feedforward Neural Network Construction Using Cross Validation
Neural Computation
Predictor output sensitivity and feature similarity-based feature selection
Fuzzy Sets and Systems
Modeling consumer situational choice of long distance communication with neural networks
Decision Support Systems
Expert Systems with Applications: An International Journal
A Hybrid Rule Extraction Method Using Rough Sets and Neural Networks
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks
Air Pollutant Level Estimation Applying a Self-organizing Neural Network
IWINAC '07 Proceedings of the 2nd international work-conference on Nature Inspired Problem-Solving Methods in Knowledge Engineering: Interplay Between Natural and Artificial Computation, Part II
Neural Information Processing
Diversity-Based Feature Selection from Neural Network with Low Computational Cost
Neural Information Processing
OWA-weighted based clustering method for classification problem
Expert Systems with Applications: An International Journal
New decision support tool for treatment intensity choice in childhood acute lymphoblastic leukemia
IEEE Transactions on Information Technology in Biomedicine
Computers & Mathematics with Applications
On preprocessing data for financial credit risk evaluation
Expert Systems with Applications: An International Journal
Breast-Cancer identification using HMM-fuzzy approach
Computers in Biology and Medicine
A new clustering algorithm for transaction data via caucus
PAKDD'03 Proceedings of the 7th Pacific-Asia conference on Advances in knowledge discovery and data mining
Pruned neural networks for regression
PRICAI'00 Proceedings of the 6th Pacific Rim international conference on Artificial intelligence
Selecting salient features for classification committees
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Feature analysis and classification of protein secondary structure data
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Relevance metrics to reduce input dimensions in artificial neural networks
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
CIRA'09 Proceedings of the 8th IEEE international conference on Computational intelligence in robotics and automation
Selecting useful features for personal credit risk analysis
International Journal of Business Information Systems
Designing an artificial immune system-based machine learning classifier for medical diagnosis
ICICA'10 Proceedings of the First international conference on Information computing and applications
A functional neural fuzzy network for classification applications
Expert Systems with Applications: An International Journal
Combining functional networks and sensitivity analysis as wrapper method for feature selection
Expert Systems with Applications: An International Journal
Investigating a novel GA-based feature selection method using improved KNN classifiers
International Journal of Information and Communication Technology
Feature subset selection wrapper based on mutual information and rough sets
Expert Systems with Applications: An International Journal
A new hybrid ant colony optimization algorithm for feature selection
Expert Systems with Applications: An International Journal
Selecting variables for neural network committees
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
A new method for feature selection
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
Difference-similitude matrix in text classification
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part II
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part II
International Journal of Data Warehousing and Mining
A survey on feature selection methods
Computers and Electrical Engineering
Journal of Computer Security
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Feature selection is an integral part of most learning algorithms. Due to the existence of irrelevant and redundant attributes, by selecting only the relevant attributes of the data, higher predictive accuracy can be expected from a machine learning method. In this paper, we propose the use of a three-layer feedforward neural network to select those input attributes that are most useful for discriminating classes in a given set of input patterns. A network pruning algorithm is the foundation of the proposed algorithm. By adding a penalty term to the error function of the network, redundant network connections can be distinguished from those relevant ones by their small weights when the network training process has been completed. A simple criterion to remove an attribute based on the accuracy rate of the network is developed. The network is retrained after removal of an attribute, and the selection process is repeated until no attribute meets the criterion for removal. Our experimental results suggest that the proposed method works very well on a wide variety of classification problems