On the stability of the travelling salesman problem algorithm of Hopfield and Tank
Biological Cybernetics
Feature Selection: Evaluation, Application, and Small Sample Performance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Artificial Intelligence Review - Special issue on lazy learning
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
Unsupervised Feature Selection Using Feature Similarity
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural-network feature selector
IEEE Transactions on Neural Networks
Input feature selection for classification problems
IEEE Transactions on Neural Networks
Analysis of new variable selection methods for discriminant analysis
Computational Statistics & Data Analysis
Different metaheuristic strategies to solve the feature selection problem
Pattern Recognition Letters
ISBRA'07 Proceedings of the 3rd international conference on Bioinformatics research and applications
Bi-objective feature selection for discriminant analysis in two-class classification
Knowledge-Based Systems
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In this paper, we investigate feature analysis for the prediction of the secondary structure of protein sequences using support vector machines (SVMs) and k-nearest neighbor algorithm (kNN). We apply feature selection and scaling techniques to obtain a number of distinct feature subsets with different features and each scaled differently. The feature selection and the scaling are performed using the mutual information (MI). We formulate the feature selection and scaling as combinatorial optimization problem and obtain solutions using a Hopfield-style algorithm. Our experimental results show that the feature subset selection improves the performance for both SVM and kNN while the feature scaling is consistently beneficial for kNN.