Statistical Pattern Recognition Toolbox (STPRtool).
Version 2.12 12-Sep-2013
Bayesian classification.
bayescls - Bayesian classifier with reject option.
bayesdf - Computes decision boundary of Bayesian classifier.
bayeserr - Computes Bayesian risk for 1D case with Gaussians.
Linear Discriminant function.
linclass - Linear classifier.
ekozinec - Kozinec's algorithm for eps-optimal hyperplane.
mperceptron - Perceptron to train multi-class linear classifier.
perceptron - Perceptron to train binary linear classifier.
fld - Fisher Linear Discriminant.
fldqp - Fisher Linear Discriminant using QP.
Generalized Anderson's task.
andrerr - Classification error of the Generalized Anderson's task.
androrig - Original method to solve the Anderson's task.
eanders - Epsilon-solution of the Generalized Anderson's task.
ganders - Solves the Generalized Anderson's task.
ggradander - Generalized gradients approach to Gen. Anderson's task.
Linear feature extraction.
linproj - Linear data projection.
lda - Linear Discriminant Analysis.
pca - Principal Component Analysis.
pcarec - Computes reconstructed vector after PCA projection.
Miscellaneous methods.
adaboost - AdaBoost algorithm.
adaclass - AdaBoost classifier.
cerror - Computes classification error.
crossval - Partions data for cross-validation.
knnclass - k-Nearest Neighbours classifier.
knnrule - Creates K-nearest neighbours classifier.
roc - Computes Receiver Operator Characteristic.
sectohms - Converts seconds to HOUR:MIN:SEC format.
weaklearner - Produces classifier thresholding single feature.
Kernel machines.
diagker - Returns diagonal of kernel matrix.
dualcov - Dual representation of covariance matrix.
dualmean - Computes dual representation of mean vector.
kdist - Computes distance between points in kernel space.
kernel - Evaluates kernel function.
kernelproj - Kernel projection.
kfd - Kernel Fisher Discriminant.
knorm - Computes L2-norm in kernel space.
kperceptr - Kernel Perceptron.
lin2svm - Merges linear rule and kernel projection.
minball - Minimal enclosing ball in kernel feature space.
rsrbf - Reduced Set Method for RBF kernel expansion.
rspoly2 - Reduced Set Method for homegeneous 2nd polynomial kernel.
Kernel feature extraction.
gda - Generalized Discriminant Analysis.
greedykpca - Greedy kernel PCA.
kpca - Kernel Principal Component Analysis.
kpcarec - Reconstructs image after kernel PCA.
Optimization methods.
gmnp - Generalized Minimal Norm (GMNP) problem.
gnnls - Generalized Non-negative Least Squares (GNNLS) problem.
gnpp - Generalized Nearest Point (GNPP) problem.
gridsearch - Function minimization using grid search.
gsmo - Generalized Sequential Minimal Optimizer.
qpbsvm - Solves QP task required for learning SVM without bias term.
qpssvm - Solves QP task required for StructSVM learning.
Pre-image problem for RBF kernel.
rbfpreimg - Schoelkopf's fixed-point algorithm.
rbfpreimg2 - Gradient optimization.
rbfpreimg3 - Kwok-Tsang's algorithm.
Support Vector Machines.
bsvm2 - Solver for multi-class BSVM with L2-soft margin.
evalsvm - Training and evaluates SVM classifier.
mvsvmclass - Majority voting multi-class SVM classifier.
oaasvm - Multi-class SVM using One-Agains-All decomposition.
oaosvm - Multi-class SVM using One-Against-One decomposition.
smo - Sequential Minimal Optimization for SVM (L1).
svm1d - Linear SVM for 1-dimensional input data.
svm2 - Solver for binary SVM with L2 soft margin.
svmclass - Support Vector Machines Classifier.
svmlight - Interface to SVM^{light} software.
svmquadprog - SVM trained by Matlab Optimization Toolbox.
Probability distribution functions and estimation.
dsamp - Generates samples from discrete distribution.
erfc2 - Normal cumulative distribution function.
gmmsamp - Generates sample from Gaussian mixture model (GMM).
gsamp - Generates sample from Gaussian distribution.
cmeans - C-means (or K-means) clustering algorithm.
mahalan - Computes Mahalanobis distance.
pdfgauss - Computes probability for Gaussian distribution.
pdfgmm - Computes probability for Gaussian mixture model.
sigmoid - Evaluates sigmoid function.
emgmm - Expectation-Maximization Algorithm for GMM.
mlcgmm - ML estimation of GMM from complete data.
mlsigmoid - Fitting a sigmoid function using ML estimation.
mmgauss - Minimax estimation of Gaussian distribution.
rsde - Reduced Set Density Estimator.
Quadratic discriminant function.
lin2quad - Merges linear rule and quadratic mapping.
qmap - Quadratic data mapping.
quadclass - Quadratic classifier.
Visualization.
pandr - Visualizes solution of the Generalized Anderson's task.
pboundary - Plots decision boundary of given classifier in 2D.
pgauss - Visualizes set of bivariate Gaussians.
pgmm - Visualizes Gaussian mixture model.
pkernelproj - Plots isolines of kernel projection.
plane3 - Plots plane in 3d.
pline - Plots line in 2D.
ppatterns - Plots pattern as points in feature space.
psvm - Plots decision boundary of binary SVM classifier.
showim - Displays given image(s).
Data sets.
andersons_task - (dir) Input for demo on Generalized Anderson's task.
binary_separable - (dir) Input for demo on Linear classification.
gmm_sample - (dir) Input for demo on EM algorithm for GMM.
iris_data - (dir) Fisher's Iris data set.
mm_sample - (dir) Input for demo on Minimax Algorithm.
multi_separable - (dir) Linearly separable multi-class data.
ocr_numerals - (dir) Examples of hand-written numerals.
riply_data - (dir) Riply's data set.
svm_sample - (dir) Input for demo on SVM.
c2s - Converts cell to structure array.
createdata - Interactive data generator.
gencircledata - Generates data on circle corrupted by Gaussian noise.
genlsdata - Generates linearly separable binary data.
mergesets - Merges data sets to one labeled data file.
savestruct - Saves fields of given structure to file.
usps2mat - Converts USPS database to Matlab data file (MAT).
Demos.
image_denoising - (dir) Image denoising using kernel PCA.
ocr - (dir) Optical Character Recognition.
demo_anderson - Generalized Anderson's task.
demo_emgmm - Expectation-Maximization algorithm for GMM.
demo_kpcadenois - Idea of image denoising based on Kernel PCA.
demo_linclass - Algorithms learning linear classifiers.
demo_mmgauss - Minimax estimation of Gaussian distribution.
demo_ocr - Run OCR demo.
demo_pcacomp - Image compression using PCA.
demo_svm - Support Vector Machines.
demo_svmpout - Fitting a posteriori probability to SVM output.
compilemex - Compiles all MEX files of the STPRtool.
stprpath - Sets path to the STPRtool.
About: Statistical Pattern Recognition Toolbox
(C) 1999-2005, Written by Vojtech Franc and Vaclav Hlavac
Czech Technical University Prague
Faculty of Electrical Engineering
Center for Machine Perception
Modifications:
09-sep-2007
16-jul-2007, VF
02-jul-2007, VF
17-jun-2007, VF
26-mar-2007, VF
20-nov-2006, VF
19-sep-2006, VF
18-sep-2006, VF
09-sep-2005, VF
06-jun-2005, VF
24-jan-2005, VF
22-dec-2004, VF
14-dec-2004, VF
08-oct-2004, VF
27-aug-2004, VF
15-jun-2004, VF
11-jun-2004, VF
20-sep-2003, VF