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
Towards automatic detection of atrial fibrillation: A hybrid computational approach
TL;DR: The proposed GP/OLS and GP/SA models have a significantly better performance than the RBF and several models found in the literature, and identify the effective time domain features of heart rate variability (HRV) signals via an improved forward floating selection analysis.
Journal ArticleDOI
A Comparison between Global and Local Features for Computational Classification of Folk Song Melodies
TL;DR: In all cases, it appears that the local approach outperforms the global approach in a classification task for melodies, which indicates that local features carry more information about the identity of melodies.
Book ChapterDOI
Fingerprint Template Protection: From Theory to Practice
TL;DR: Though much progress has been made over the last decade, it is believed that fingerprint template protection algorithms are still not sufficiently robust to be incorporated into practical fingerprint recognition systems.
Journal ArticleDOI
Information Loss of the Mahalanobis Distance in High Dimensions: Application to Feature Selection
TL;DR: The information loss is exploited then to set a lower limit for the correct classification rate achieved by the Bayes classifier that is used in subset feature selection.
Journal ArticleDOI
Heterogeneous hand gesture recognition using 3D dynamic skeletal data
TL;DR: This work uses the natural structure of the hand topology – called later hand skeletal data – to extract effective hand kinematic descriptors from the gesture sequence and introduces a prior gesture detection phase achieved using a binary classifier before the final gesture recognition.
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.