Estimating attributes: analysis and extensions of RELIEF
ECML-94 Proceedings of the European conference on machine learning on Machine Learning
Floating search methods in feature selection
Pattern Recognition Letters
Machine Learning
Divergence Based Feature Selection for Multimodal Class Densities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Selection of relevant features and examples in machine learning
Artificial Intelligence - Special issue on relevance
Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
Data Mining and Knowledge Discovery with Evolutionary Algorithms
Data Mining and Knowledge Discovery with Evolutionary Algorithms
Recent approaches to global optimization problems through Particle Swarm Optimization
Natural Computing: an international journal
Feature Subset Selection Using a Genetic Algorithm
IEEE Intelligent Systems
A Note on the Universal Approximation Capability of Support Vector Machines
Neural Processing Letters
On the Learnability and Design of Output Codes for Multiclass Problems
COLT '00 Proceedings of the Thirteenth Annual Conference on Computational Learning Theory
A New Multi-Class SVM Based on a Uniform Convergence Result
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 4 - Volume 4
Asymptotic behaviors of support vector machines with Gaussian kernel
Neural Computation
An introduction to variable and feature selection
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
The Cross Entropy Method: A Unified Approach To Combinatorial Optimization, Monte-carlo Simulation (Information Science and Statistics)
Simulation optimization: a review, new developments, and applications
WSC '05 Proceedings of the 37th conference on Winter simulation
Feature selection based on rough sets and particle swarm optimization
Pattern Recognition Letters
Cross entropy guided ant-like agents finding dependable primary/backup path patterns in networks
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Improved binary PSO for feature selection using gene expression data
Computational Biology and Chemistry
The feature selection problem: traditional methods and a new algorithm
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Two-Step Cross-Entropy Feature Selection for Microarrays—Power Through Complementarity
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
Nearest neighbor pattern classification
IEEE Transactions on Information Theory
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Many data mining applications involve the task of building a model for predictive classification. The goal of this model is to classify data instances into classes or categories of the same type. The use of variables not related to the classes can reduce the accuracy and reliability of classification or prediction model. Superfluous variables can also increase the costs of building a model particularly on large datasets. The feature selection and hyper-parameters optimization problem can be solved by either an exhaustive search over all parameter values or an optimization procedure that explores only a finite subset of the possible values. The objective of this research is to simultaneously optimize the hyper-parameters and feature subset without degrading the generalization performances of the induction algorithm. We present a global optimization approach based on the use of Cross-Entropy Method to solve this kind of problem.