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
More filters
Journal ArticleDOI
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: In this article, the authors focus on the two leading chronic diseases, heart disease and diabetes, and develop data-driven methods to predict hospitalizations due to these conditions using Electronic Health Records (EHRs).
Journal ArticleDOI
A novel approach to hyperspectral band selection based on spectral shape similarity analysis and fast branch and bound search
TL;DR: This paper proposes an effective band selection method from the novel perspective of spectral shape similarity analysis with key points extraction and thus retains physical information of hyperspectral remote sensing images.
Journal ArticleDOI
Target-Constrained Interference-Minimized Band Selection for Hyperspectral Target Detection
TL;DR: A new approach called target-constrained interference-minimized BS (TCIMBS) is developed which can be used to select band subset for specific target detection, while annihilating targets of no interest and suppressing interferers and background.
Journal Article
Correlation-based feature selection strategy in classification problems
TL;DR: Experimental results show that, in most cases, it is possible to lower computation time and that with high statistical significance the quality of the selected feature sets is not lower compared with those selected using the unmodified pairwise selection process.
Journal ArticleDOI
Multiple extreme learning machines for a two-class imbalance corporate life cycle prediction
TL;DR: The proposed model - namely, the multiple extreme learning machines (MELMs) - shows promising performance under numerous assessing criteria, but one critical defect of the ensemble classifier is that it lacks comprehensibility.
References
More filters
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.