Journal ArticleDOI
Floating search methods in feature selection
TLDR
Sequential search methods characterized by a dynamically changing number of features included or eliminated at each step, henceforth "floating" methods, are presented and are shown to give very good results and to be computationally more effective than the branch and bound method.About:
This article is published in Pattern Recognition Letters.The article was published on 1994-11-01. It has received 3104 citations till now. The article focuses on the topics: Beam search & Jump search.read more
Citations
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Journal ArticleDOI
Generalized T2 test for genome association studies.
TL;DR: A generalized T2 statistic is presented, which can utilize multiple SNP markers simultaneously and considers the effects of multiple disease-susceptibility loci and has a close relationship to discriminant analysis and common measure of genetic distance.
Journal ArticleDOI
Feature Subset Selection and Ranking for Data Dimensionality Reduction
Proceedings ArticleDOI
Algorithms for feature selection: An evaluation
D. Zongker,Anil K. Jain +1 more
TL;DR: The results show that the sequential forward floating selection (SFFS) algorithm, proposed by Pudil et al. (1994), dominates the other algorithms tested, and illustrates the dangers of using feature selection in small sample size situations.
Journal ArticleDOI
Particle Swarm Optimization-Based Hyperspectral Dimensionality Reduction for Urban Land Cover Classification
He Yang,Qian Du,Genshe Chen +2 more
TL;DR: In these experiments, SVM classification accuracy using PSO-selected bands is greatly higher than using all of the original bands or dimensionality-reduced data from principal component analysis (PCA) or linear discriminant analysis (LDA), and the improvement on SVM accuracy can bring out even more significant improvement in classifier fusion.
Journal ArticleDOI
Unobtrusive Assessment of Students' Emotional Engagement during Lectures Using Electrodermal Activity Sensors
TL;DR: This paper shows that off-the-shelf wearable devices can be used to unobtrusively monitor the emotional engagement of students during lectures and proposes the use of several novel features to capture students' momentary engagement.
References
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Journal ArticleDOI
A Branch and Bound Algorithm for Feature Subset Selection
TL;DR: In this paper, a branch and bound-based feature subset selection algorithm is proposed to select the best subset of m features from an n-feature set without exhaustive search, which is computationally computationally unfeasible.
Journal ArticleDOI
A note on genetic algorithms for large-scale feature selection
W. Siedlecki,Jack Sklansky +1 more
TL;DR: The preliminary results suggest that GA is a powerful means of reducing the time for finding near-optimal subsets of features from large sets.
Journal ArticleDOI
A Direct Method of Nonparametric Measurement Selection
TL;DR: A direct method of measurement selection is proposed to determine the best subset of d measurements out of a set of D total measurements, using a nonparametric estimate of the probability of error given a finite design sample set.
Journal ArticleDOI
On the effectiveness of receptors in recognition systems
T. Marill,D. Green +1 more
TL;DR: Some of the theoretical problems encountered in trying to determine a more formal measure of the effectiveness of a set of tests are discussed; a measure which might be a practical substitute for the empirical evaluation.
Journal ArticleDOI
On automatic feature selection
W. Siedlecki,Jack Sklansky +1 more
TL;DR: In this paper, a review of feature selection for multidimensional pattern classification is presented, and the potential benefits of Monte Carlo approaches such as simulated annealing and genetic algorithms are compared.