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.

## Project Files:

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