Linear discriminant analysis (LDA) and the related Fisher's linear discriminant are methods used in statistics, pattern recognition and machine learning to find a linear combination of features which characterizes or separates two or more classes of objects or events. The resulting combination may be used as a linear classifier, or, more commonly, for dimensionality reduction before later classification.
The following matlab project contains the source code and matlab examples used for lda.
The source code and files included in this project are listed in the project files section, please make sure whether the listed source code meet your needs there.
Linear discriminent analysis by using the example of a flower. in matlab
Lda (linear discriminant analysis) in matlab
Multiclass lda in matlab
Lda linear discriminant analysis in matlab
Fda lda multiclass in matlab
Linear discriminant analysis code in matlab
Lda for high dimension small sample size data in matlab
This is version 0.3 of the discriminant analysis toolbox with major bug fixes. in matlab
Fischer linear dicriminant analysis in matlab
Fast null linear discriminant analysis in matlab
Uncorrelated multilinear discriminant analysis (umlda) in matlab
Bayesian robust simplicial mixture model in matlab
Mexing with ifort 11.0 in 64 bit matlab
Heston model calibration and simulation in matlab
Fld based face recognition system in matlab
Qr rq ql lq factorizations in matlab