The nature of statistical learning theory
The nature of statistical learning theory
Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
Pairwise classification and support vector machines
Advances in kernel methods
Ant algorithms for discrete optimization
Artificial Life
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Feature Selection for Knowledge Discovery and Data Mining
Feature Selection for Knowledge Discovery and Data Mining
On Comparing Classifiers: Pitfalls toAvoid and a Recommended Approach
Data Mining and Knowledge Discovery
A Simple Decomposition Method for Support Vector Machines
Machine Learning
Feature Subset Selection Using a Genetic Algorithm
IEEE Intelligent Systems
Further Research on Feature Selection and Classification Using Genetic Algorithms
Proceedings of the 5th International Conference on Genetic Algorithms
The Ant Colony Metaphor for Searching Continuous Design Spaces
Selected Papers from AISB Workshop on Evolutionary Computing
Efficient svm training using low-rank kernel representations
The Journal of Machine Learning Research
Feature Selection for Support Vector Machines by Means of Genetic Algorithms
ICTAI '03 Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence
Ant Colony Optimization
A hybrid approach for feature subset selection using neural networks and ant colony optimization
Expert Systems with Applications: An International Journal
SVM optimization: inverse dependence on training set size
Proceedings of the 25th international conference on Machine learning
Fuzzy-rough data reduction with ant colony optimization
Fuzzy Sets and Systems
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Webpage classification with ACO-enhanced fuzzy-rough feature selection
RSCTC'06 Proceedings of the 5th international conference on Rough Sets and Current Trends in Computing
Artificial life feature selection techniques for prostrate cancer diagnosis using TRUS images
ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
A method for solving optimization problem in continuous space using improved ant colony algorithm
CASDMKM'04 Proceedings of the 2004 Chinese academy of sciences conference on Data Mining and Knowledge Management
Neural networks for classification: a survey
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
SVM classifier based feature selection using GA, ACO and PSO for siRNA design
ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part II
Computer Methods and Programs in Biomedicine
Efficient ant colony optimization for image feature selection
Signal Processing
Hybridising harmony search with a Markov blanket for gene selection problems
Information Sciences: an International Journal
| Hi-index | 0.01 |
This work presents a novel hybrid ACO-based classifier model that combines ant colony optimization (ACO) and support vector machines (SVM) to improve classification accuracy with a small and appropriate feature subset. To simultaneously optimize the feature subset and the SVM kernel parameters, the feature importance and the pheromones are used to determine the transition probability; the classification accuracy and the weight vector of the feature provided by the SVM classifier are both considered to update the pheromone. The experimental results indicate that the hybridized approach can correctly select the discriminating input features and also achieve high classification accuracy.