Software - QDA/LDA Discriminant Analysis

This page contains software for Matlab for classifying data points using QDA/LDA classifiers, described in [1]. See the page about QDA/LDA classifiers for further details. Download the following code:

qdalda_train.m	Finds the bootstrap resampled parameters for (Fisher's) linear or quadratic discriminant analysis.
qdalda_classify.m	Classifies the given data points according to the parameters for the modelled classes found using qdalda_train.m above.
qdalda_traintest.m	Performs training and testing of a QDA/LDA classifier applied to the given data points. Returns the correct classification performance with confidence intervals.
qdalda_plotdb.m	Plots the given data points and the classification boundary for a trained QDA/LDA classifier for 2-D data sets.
qdalda_demo.m	Demonstrates how to use the above routines.

Typing 'help (function name)' shows instructions for each routine.

[1] C.M. Bishop (1995), Neural Networks for Pattern Recognition. Oxford, New York: Clarendon Press; Oxford University Press. 482.