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… (More)
Wikipedia

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2007
Highly Cited
2007
Linear Discriminant Analysis (LDA) is a well-known method for dimensionality reduction and classification. LDA in the binaryclass… (More)
  • table 1
  • table 2
  • table 3
Is this relevant?
Highly Cited
2007
Highly Cited
2007
Many current face recognition algorithms perform badly when the lighting or pose of the probe and gallery images differ. In this… (More)
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • table 1
Is this relevant?
Highly Cited
2007
Highly Cited
2007
Linear Discriminant Analysis (LDA) has been a popular method for extracting features which preserve class separability. The… (More)
  • figure 1
  • table 1
  • figure 2
Is this relevant?
Highly Cited
2006
Highly Cited
2006
Linear dimensionality reduction methods, such as LDA, are often used in object recognition for feature extraction, but do not… (More)
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
Is this relevant?
Highly Cited
2005
Highly Cited
2005
This paper proposes an innovative algorithm named 2D-LDA, which directly extracts the proper features from image matrices based… (More)
  • figure 1
  • figure 2
  • table 1
  • figure 3
Is this relevant?
Highly Cited
2004
Highly Cited
2004
Linear Discriminant Analysis (LDA) is a well-known scheme for feature extraction and dimension reduction. It has been used widely… (More)
  • table 1
  • figure 1
  • figure 2
  • table 2
Is this relevant?
Highly Cited
2000
Highly Cited
2000
We present a new method that we call generalized discriminant analysis (GDA) to deal with nonlinear discriminant analysis using… (More)
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
Is this relevant?
Highly Cited
1999
Highly Cited
1999
In this paper we describe a holistic face recognition method based on subspace Linear Dis-criminant Analysis (LDA). The method… (More)
  • figure 2
Is this relevant?
Highly Cited
1995
Highly Cited
1995
Nearest neighbor classification expects the class conditional probabilities to be locally constant, and suffers from bias in high… (More)
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
Is this relevant?
Highly Cited
1989
Highly Cited
1989
Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org… (More)
  • table 1
  • table 2
  • table 4
  • table 5
  • table 6
Is this relevant?