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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Nonlinear phonocardiographic Signal Processing
TL;DR: The aim of this thesis work has been to develop signal analysis methods for a computerized cardiac auscultation system, the intelligent stethoscope, and in particular, the work focuses on classificatio ...
Book ChapterDOI
On Feature Selection with Measurement Cost and Grouped Features
TL;DR: It is shown, that employing grouping improves the performance significantly for low measurement costs and an application where limiting the computation time is a very important topic: the segmentation of backscatter images in product analysis is discussed.
Journal ArticleDOI
Detection of antibiotic resistant Escherichia Coli bacteria using infrared microscopy and advanced multivariate analysis
Ahmad Salman,Uraib Sharaha,Eladio Rodriguez-Diaz,Eladio Rodriguez-Diaz,E. Shufan,Klaris Riesenberg,Irving J. Bigio,Mahmoud Huleihel +7 more
TL;DR: This study provides proof-of-concept evidence for the translational potential of this spectroscopic technique in the clinical management of bacterial infections, by characterizing and classifying antibiotic resistance in a much shorter time than possible with current standard laboratory methods.
Journal ArticleDOI
Towards a ternary NIRS-BCI: single-trial classification of verbal fluency task, Stroop task and unconstrained rest.
TL;DR: The results suggest that effective communication can be achieved with a ternary NIRS-BCI that supports VFT, Stroop task and rest via measurements from the frontal and parietal cortices, improving the practicality of this technology.
Journal ArticleDOI
Using multiscale texture and density features for near-term breast cancer risk analysis.
Wenqing Sun,Tzu-Liang Bill Tseng,Wei Qian,Jianying Zhang,Edward C Saltzstein,Bin Zheng,Fleming Lure,Hui Yu,Shi Zhou +8 more
TL;DR: The study results demonstrated a moderately high positive association between risk prediction scores generated by the quantitative multiscale mammographic image feature analysis and the actual risk of a woman having an image-detectable breast cancer in the next subsequent examinations.
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.