Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Hypothesis-driven constructive induction
Hypothesis-driven constructive induction
Genetic programming II (videotape): the next generation
Genetic programming II (videotape): the next generation
Using genetic algorithms for restructuring feature-based representation space
Using genetic algorithms for restructuring feature-based representation space
Using learning to facilitate the evolution of features for recognizing visual concepts
Evolutionary Computation
Hybrid learning using genetic algorithms and decision trees for pattern classification
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Machine Learning - Special issue on multistrategy learning
Data filtering for automatic classification of rocks from reflectance spectra
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Face Recognition Using Support Vector Machines with the Feature Set Extracted by Genetic Algorithms
AVBPA '01 Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication
Toward Global Optimization of Case-Based Reasoning Systems for Financial Forecasting
Applied Intelligence
Feature construction for reduction of tabular knowledge-based systems
Information Sciences—Informatics and Computer Science: An International Journal
Constructive induction and genetic algorithms for learning concepts with complex interaction
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Classification and filtering of spectra: A case study in mineralogy
Intelligent Data Analysis
Reducing complex attribute interaction through non-algebraic feature construction
AIAP'07 Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: artificial intelligence and applications
A Genetic-Based Feature Construction Method for Data Summarisation
ADMA '08 Proceedings of the 4th international conference on Advanced Data Mining and Applications
Dynamic Aggregation of Relational Attributes Based on Feature Construction
ADBIS '08 Proceedings of the 12th East European conference on Advances in Databases and Information Systems
Feature Construction and Feature Selection in Presence of Attribute Interactions
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
Evolutionary multi-feature construction for data reduction: A case study
Applied Soft Computing
A direct evolutionary feature extraction algorithm for classifying high dimensional data
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Evolutionary discriminant feature extraction with application to face recognition
EURASIP Journal on Advances in Signal Processing - Special issue on recent advances in biometric systems: a signal processing perspective
Dimensionality reduction via genetic value clustering
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Feature generation in fault diagnosis based on immune programming
CIRA'09 Proceedings of the 8th IEEE international conference on Computational intelligence in robotics and automation
An effective colour feature extraction method using evolutionary computation for face recognition
International Journal of Biometrics
Self-tuned Evolution-COnstructed features for general object recognition
Pattern Recognition
Simultaneous optimization of artificial neural networks for financial forecasting
Applied Intelligence
PSO for feature construction and binary classification
Proceedings of the 15th annual conference on Genetic and evolutionary computation
A feature construction method for general object recognition
Pattern Recognition
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The authors present Genetic Algorithm Based Representation Transformation (GABRET), the system they created to transform feature spaces to improve classification techniques. Depending on the problem, the system applies either a feature-selection or ýconstruction module to search the problem space and improve the recognition rate. Both methods are based on genetic algorithms that use an evaluation function as feedback to guide the search. The authors test this method on an eye-detection face recognition system, demonstrating substantially better classification rates than competing systems.