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Linear discriminant analysis

Known as: Fisher discriminant analysis, Fisher linear discriminant, Multiclass LDA 
Linear discriminant analysis (LDA) is a generalization of Fisher's linear discriminant, a method used in statistics, pattern recognition and machine… 
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Related topics

Related topics

44 relations
ArrayTrackBrain–computer interfaceCategorical variableData mining

Broader (1)

Statistical classification

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Review
2014
Review
2014
Unifying Probabilistic Linear Discriminant Analysis Variants in Biometric Authentication
Probabilistic linear discriminant analysis PLDA is commonly used in biometric authentication. We review three PLDA variants… 
Highly Cited
2012
Highly Cited
2012
Brain tumor MRI image classification with feature selection and extraction using linear discriminant analysis
Feature extraction is a method of capturing visual content of an image. The feature extraction is the process to represent raw… 
Highly Cited
2011
Highly Cited
2011
Distributed linear discriminant analysis
Linear discriminant analysis (LDA) is a widely used feature extraction method for classification. We introduce distributed… 
Highly Cited
2011
Highly Cited
2011
Speed up kernel discriminant analysis
Linear discriminant analysis (LDA) has been a popular method for dimensionality reduction, which preserves class separability… 
Highly Cited
2010
Highly Cited
2010
Multi-label Linear Discriminant Analysis
Multi-label problems arise frequently in image and video annotations, and many other related applications such as multi-topic… 
Highly Cited
2010
Highly Cited
2010
Feature Selection Based on Linear Discriminant Analysis
In this paper we propose a novel feature selection method based on linear discriminant analysis (LDA). To view feature selection… 
Highly Cited
2008
Highly Cited
2008
Training Linear Discriminant Analysis in Linear Time
Linear Discriminant Analysis (LDA) has been a popular method for extracting features which preserve class separability. It has… 
Highly Cited
2007
Highly Cited
2007
Modified Fisher's Linear Discriminant Analysis for Hyperspectral Imagery
In this letter, we present a modified Fisher's linear discriminant analysis (MFLDA) for dimension reduction in hyperspectral… 
Highly Cited
2006
Highly Cited
2006
Feature Reduction via Generalized Uncorrelated Linear Discriminant Analysis
High-dimensional data appear in many applications of data mining, machine learning, and bioinformatics. Feature reduction is… 
Highly Cited
2004
Highly Cited
2004
Comparison of logistic regression and linear discriminant analysis
Two of the most widely used statistical methods for analyzing categorical outcome variables are linear discriminant analysis and… 
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