Journal ArticleDOI
Modified binary PSO for feature selection using SVM applied to mortality prediction of septic patients
TLDR
An enhanced version of binary particle swarm optimization, designed to cope with premature convergence of the BPSO algorithm is proposed, which can correctly select the discriminating input features and also achieve high classification accuracy.About:
This article is published in Applied Soft Computing.The article was published on 2013-08-01. It has received 256 citations till now. The article focuses on the topics: Multi-swarm optimization & Particle swarm optimization.read more
Citations
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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
Metaheuristic design of feedforward neural networks
TL;DR: A broad spectrum of FNN optimization methodologies including conventional and metaheuristic approaches are summarized, which provides interesting research challenges for future research to cope-up with the present information processing era.
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Binary PSO with mutation operator for feature selection using decision tree applied to spam detection
TL;DR: A novel spam detection method that focused on reducing the false positive error of mislabeling nonspam as spam, which demonstrated the MBPSO is superior to GA, RSA, PSO, and BPSO in terms of classification performance and wrappers are more effective than filters with regard to classification performance indexes.
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A hybrid particle swarm optimization for feature subset selection by integrating a novel local search strategy
Parham Moradi,Mozhgan Gholampour +1 more
TL;DR: The proposed hybrid feature selection algorithm, called HPSO-LS, uses a local search technique which is embedded in particle swarm optimization to select the reduced sized and salient feature subset to enhance the search process near global optima.
Journal ArticleDOI
Swarm Intelligence Algorithms for Feature Selection: A Review
TL;DR: A unified SI framework is proposed and used to explain different approaches to FS and guidelines on how to develop SI approaches for FS are provided to support researchers and analysts in their data mining tasks and endeavors.
References
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Journal ArticleDOI
A Tutorial on Support Vector Machines for Pattern Recognition
TL;DR: There are several arguments which support the observed high accuracy of SVMs, which are reviewed and numerous examples and proofs of most of the key theorems are given.
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Definitions for Sepsis and Organ Failure and Guidelines for the Use of Innovative Therapies in Sepsis
Roger C. Bone,Robert A. Balk,F. B. Cerra,R. P. Dellinger,A. M. Fein,William A. Knaus,Roland M. H. Schein,W. J. Sibbald +7 more
TL;DR: An American College of Chest Physicians/Society of Critical Care Medicine Consensus Conference was held in Northbrook in August 1991 with the goal of agreeing on a set of definitions that could be applied to patients with sepsis and its sequelae as mentioned in this paper.
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Wrappers for feature subset selection
Ron Kohavi,George H. John +1 more
TL;DR: The wrapper method searches for an optimal feature subset tailored to a particular algorithm and a domain and compares the wrapper approach to induction without feature subset selection and to Relief, a filter approach tofeature subset selection.
Journal ArticleDOI
Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of care.
Derek C. Angus,Walter T. Linde-Zwirble,Jeffrey Lidicker,Gilles Clermont,Joseph A. Carcillo,Michael R. Pinsky +5 more
TL;DR: Severe sepsis is a common, expensive, and frequently fatal condition, with as many deaths annually as those from acute myocardial infarction, and is especially common in the elderly and is likely to increase substantially as the U.S. population ages.