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
Radiomics-based features for pattern recognition of lung cancer histopathology and metastases.
José Raniery Ferreira Junior,Marcel Koenigkam-Santos,Federico Enrique Garcia Cipriano,Alexandre Todorovic Fabro,Paulo Mazzoncini de Azevedo-Marques +4 more
TL;DR: The radiomics characterization approach presented great potential to be used in a computational model to aid lung cancer histopathological subtype diagnosis as a "virtual biopsy" and metastatic prediction for therapy decision support without the necessity of a whole-body imaging scanning.
Journal ArticleDOI
A novel feature-based approach to characterize algorithm performance for the traveling salesperson problem
TL;DR: This paper contributes to the understanding of the success of 2-opt based local search algorithms for solving the traveling salesperson problem with a statistical approach and examines the features of TSP instances that make the problem either hard or easy to solve.
Journal ArticleDOI
Review of classical dimensionality reduction and sample selection methods for large-scale data processing
TL;DR: The paper primarily introduces the application frameworks that combine sample selection and dimensionality reduction in the context of two aspects: sequential and simultaneous, which almost all get the ideal results in the processing of the large-scale training data contrasting to the original models
Journal ArticleDOI
Dynamic control of wind turbines
Andrew Kusiak,Wenyan Li,Zhe Song +2 more
TL;DR: To enhance the control strategy of the intelligent system, a multi-objective model is proposed that involves five different objectives with different weights controlling the wind turbine performance.
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Predicting individualized clinical measures by a generalized prediction framework and multimodal fusion of MRI data.
Meng Xing,Rongtao Jiang,Dongdong Lin,Juan R. Bustillo,Thomas Jones,Jiayu Chen,Qingbao Yu,Yuhui Du,Yu Zhang,Tianzi Jiang,Jing Sui,Jing Sui,Vince D. Calhoun +12 more
TL;DR: A generalized framework that can predict explicit values of clinical measures using MRI by taking advantage of joint information from multiple modalities is proposed, which enables whole brain voxel‐wise searching and achieves higher prediction accuracy and enables individualized prediction on multiple clinical measures.
References
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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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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.
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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.