Journal ArticleDOI
A Direct Method of Nonparametric Measurement Selection
TLDR
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.Abstract:
A direct method of measurement selection is proposed to determine the best subset of d measurements out of a set of D total measurements. The measurement subset evaluation procedure directly employs a nonparametric estimate of the probability of error given a finite design sample set. A suboptimum measurement subset search procedure is employed to reduce the number of subsets to be evaluated. Teh primary advantage of the approach is the direct but nonparametric evaluation of measurement subsets, for the M class problem.read more
Citations
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Journal ArticleDOI
Ridge-based vessel segmentation in color images of the retina
TL;DR: A method is presented for automated segmentation of vessels in two-dimensional color images of the retina based on extraction of image ridges, which coincide approximately with vessel centerlines, which is compared with two recently published rule-based methods.
Journal ArticleDOI
Floating search methods in feature selection
TL;DR: 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.
Journal ArticleDOI
A Survey on Evolutionary Computation Approaches to Feature Selection
TL;DR: This paper presents a comprehensive survey of the state-of-the-art work on EC for feature selection, which identifies the contributions of these different algorithms.
Journal ArticleDOI
Particle Swarm Optimization for Feature Selection in Classification: A Multi-Objective Approach
TL;DR: The experimental results show that the two PSO-based multi-objective algorithms can automatically evolve a set of nondominated solutions and the first algorithm outperforms the two conventional methods, the single objective method, and the two-stage algorithm.
Journal ArticleDOI
A Review of Feature Selection Methods Based on Mutual Information
Jorge Vergara,Pablo A. Estevez +1 more
TL;DR: This work presents a review of the state of the art of information-theoretic feature selection methods, and describes a unifying theoretical framework which can retrofit successful heuristic criteria, indicating the approximations made by each method.
References
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Journal ArticleDOI
Nearest neighbor pattern classification
Thomas M. Cover,Peter E. Hart +1 more
TL;DR: The nearest neighbor decision rule assigns to an unclassified sample point the classification of the nearest of a set of previously classified points, so it may be said that half the classification information in an infinite sample set is contained in the nearest neighbor.
Journal ArticleDOI
Estimation of Error Rates in Discriminant Analysis
TL;DR: In this article, several methods of estimating error rates in discriminant analysis are evaluated by sampling methods, and two methods in most common use are found to be significantly poorer than some new methods that are proposed.
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 dimensionality and sample size in statistical pattern classification
TL;DR: A spectrum of possibilities has been demonstrated, placing several apparently conflicting recent results in perspective.
Journal ArticleDOI
The characteristic selection problem in recognition systems
TL;DR: This paper examines the notion of a single number statistic for each characteristic which would have certain desirable properties related to the "goodness" of the characteristic, and shows that, in general, no such statistic exists.