Wrappers for feature subset selection
Ron Kohavi,George H. John +1 more
TLDR
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.About:
This article is published in Artificial Intelligence.The article was published on 1997-12-01 and is currently open access. It has received 8610 citations till now. The article focuses on the topics: Feature selection & Minimum redundancy feature selection.read more
Citations
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Journal ArticleDOI
Incremental feature selection based on rough set in dynamic incomplete data
Wenhao Shu,Hong Shen,Hong Shen +2 more
TL;DR: This work proposes an incremental approach for feature selection, which can accelerate the feature selection process in dynamic incomplete data and shows that the proposed algorithms compare favorably with that of applying the existing non-incremental methods.
Proceedings Article
Feature Selection as a Preprocessing Step for Hierarchical Clustering
TL;DR: Analysis of the particular beneets that feature selection may provide in hierarchical clustering tasks and the power of feature selection methods applied as a prepro-cessing step under the proposed dimensions suggest thatfeature selection as preprocessing only provides limited improvements in the performance task.
Journal ArticleDOI
Sleep staging from Heart Rate Variability: time-varying spectral features and Hidden Markov Models
Martin O. Mendez,Matteo Matteucci,Vincenza Castronovo,Luigi Ferini-Strambi,Sergio Cerutti,Anna M. Bianchi +5 more
TL;DR: An alternative DSS which models the behaviour of the Heart Rate Variability (HRV) signal linked to stable (NREM) and instable (REM) cerebral waves during sleep and a probabilistic model of the sleep stages transitions for decision was developed.
Journal ArticleDOI
Detection of surface defects on raw steel blocks using Bayesian network classifiers
TL;DR: An approach that detects surface defects with three-dimensional characteristics on scale-covered steel blocks and shows that the selective unrestricted Bayesian network classifier outperforms the naïve Bayes and the tree-augmented naive Bayes decision rules concerning the classification rate.
Journal ArticleDOI
Motor Imagery EEG Signals Decoding by Multivariate Empirical Wavelet Transform-Based Framework for Robust Brain–Computer Interfaces
Muhammad Tariq Sadiq,Xiaojun Yu,Zhaohui Yuan,Fan Ze-ming,Ateeq Ur Rehman,Inam Ullah,Guoqi Li,Gaoxi Xiao +7 more
TL;DR: A robust and simple automated multivariate empirical wavelet transform (MEWT) algorithm for the decoding of different MI tasks and a robust correlation-based feature selection strategy is applied to largely reduce the system complexity and computational load.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
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Classification and Regression Trees.
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C4.5: Programs for Machine Learning
TL;DR: A complete guide to the C4.5 system as implemented in C for the UNIX environment, which starts from simple core learning methods and shows how they can be elaborated and extended to deal with typical problems such as missing data and over hitting.
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Applied Regression Analysis
Norman R. Draper,Harry Smith +1 more
TL;DR: In this article, the Straight Line Case is used to fit a straight line by least squares, and the Durbin-Watson Test is used for checking the straight line fit.
Journal ArticleDOI
Induction of Decision Trees
TL;DR: In this paper, an approach to synthesizing decision trees that has been used in a variety of systems, and it describes one such system, ID3, in detail, is described, and a reported shortcoming of the basic algorithm is discussed.