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
Prediction of catalytic residues using Support Vector Machine with selected protein sequence and structural properties
Natalia V. Petrova,Cathy H. Wu +1 more
TL;DR: A novel method for the prediction of catalytic sites, using a carefully selected, supervised machine learning algorithm coupled with an optimal discriminative set of protein sequence conservation and structural properties is presented.
Journal ArticleDOI
The use of CART and multivariate regression trees for supervised and unsupervised feature selection
TL;DR: It is demonstrated how these approaches can improve (the detection of) the cluster structure in data and how they can be used for knowledge discovery.
Journal ArticleDOI
Feature Selection by Maximizing Independent Classification Information
TL;DR: A new information term denoted as Independent Classification Information is proposed that assembles the newly provided information and the preserved information negatively correlated with the redundant information to find the predictive features providing large new information and little redundancy.
Book ChapterDOI
Semi-supervised local fisher discriminant analysis for dimensionality reduction
TL;DR: This paper proposes a semi-supervised dimensionality reduction method which preserves the global structure of unlabeled samples in addition to separating labeled samples in different classes from each other and it can be computed based on eigendecompositions.
Patent
Method system and computer program product for visualizing an evidence classifier
TL;DR: In this article, an evidence visualization tool uses the visualization data files to display an evidence pane and/or a label probability pane, showing a normalized conditional probability of each label value, for each attribute value.
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.
Journal ArticleDOI
Classification and Regression Trees.
Book
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.
Book
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.