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
Hypnogram and Sleep Parameter Computation From Activity and Cardiovascular Data
TL;DR: Two methods are described; the first deals with the problem of the hypnogram estimation and the second is specifically designed to compute the sleep parameters, outperforming the traditional estimation approach based on the Hypnogram.
UCCA: A Semantics-based Grammatical Annotation Scheme
Omri Abend,Ari Rappoport +1 more
TL;DR: A simple semantic annotation scheme, UCCA for Universal Conceptual Cognitive Annotation, that covers many of the most important elements and relations present in linguistic utterances, including verb-argument structure, optional adjuncts such as adverbials, clause embeddings, and the linkage between them is proposed.
Proceedings ArticleDOI
Comparison of genetic algorithm and sequential search methods for classifier subset selection
TL;DR: This study investigates the search efficiency of genetical algorithm (GA) and sequential search methods for CSS and shows that inrespect of optimality, no method wins others in all cases.
Journal ArticleDOI
Combining EO-1 Hyperion and Envisat ASAR data for mangrove species classification in Mai Po Ramsar Site, Hong Kong
Frankie Kwan Kit Wong,Tung Fung +1 more
TL;DR: In this article, the authors explored the potential of combining hyperspectral (Earth-observing (EO)-1 Hyperion) and multi-temporal synthetic aperture radar (SAR) data, supported by in situ field surveys, to map mangrove species.
Journal ArticleDOI
Acoustical Emission Analysis by Unsupervised Graph Mining: A Novel Biomarker of Knee Health Status.
Sinan Hersek,Maziyar Baran Pouyan,Caitlin N. Teague,Michael N. Sawka,Mindy L. Millard-Stafford,Geza F. Kogler,Paul Wolkoff,Omer T. Inan +7 more
TL;DR: Unsupervised graph mining to extract GCF from knee acoustical emissions provides a novel, objective, and quantitative biomarker of knee injury and recovery that can be incorporated with a wearable joint health system for use outside of clinical settings, and austere/under resourced conditions, to aid treatment/therapy.
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.