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
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Predicting Chronic Disease Hospitalizations from Electronic Health Records: An Interpretable Classification Approach
Theodora S. Brisimi,Tingting Xu,Taiyao Wang,Wuyang Dai,William G. Adams,Ioannis Ch. Paschalidis +5 more
TL;DR: Two novel methods to predict hospitalizations due to chronic diseases, heart disease and diabetes, are proposed: $K$ -LRT, a likelihood ratio test-based method, and a Joint Clustering and Classification (JCC) method which identifies hidden patient clusters and adapts classifiers to each cluster.
Journal ArticleDOI
Polarimetric classification of Boreal forest using nonparametric feature selection and multiple classifiers
TL;DR: It is demonstrated that classification accuracies are significantly higher when leaf-on and leaf-off images are combined over a single season image and the feature selection step improves classification accuracy significantly over a baseline classifier.
Journal ArticleDOI
Optimization of nearest neighbor classifiers via metaheuristic algorithms for credit risk assessment
Yannis Marinakis,Magdalene Marinaki,Michael Doumpos,Nikolaos F. Matsatsinis,Constantin Zopounidis +4 more
TL;DR: The proposed algorithms are tested using data from 1411 firms derived from the loan portfolio of a leading Greek Commercial Bank in order to classify the firms in different groups representing different levels of credit risk.
Journal ArticleDOI
Validation of Computational Methods in Genomics
TL;DR: This paper treats the validation issue as it appears in two classes of inference algorithms relating to genomics - classification and clustering, and formulates the problem and reviews salient results.
Processing of the Phonocardiographic Signal : methods for the intelligent stethoscope
TL;DR: Phonocardiographic signals contain bioacoustic information reflecting the operation of the heart, and additional sounds indicate disease.
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.