%parzenml    Optimization of smoothing parameter in Parzen density estimation.%pca         Principal Component Analysis%pcaklm      Back en routine for PC and KL mappings%proxm       Proximity mapping and kernel construction%reducm      Reduce to minimal space mapping%remoutl     Remove outliers%rejectm     Creates rejecting mapping%scalem      Compute scaling data%sigm        Simoid mapping%spatm       Augment image dataset with spatial label information%userkernel  User supplied kernel definition%%gtm         Fit a Generative Topographic Mapping (GTM) by EM%plotgtm     Plot a Generative Topographic Mapping in 2D%som         Simple routine computing a Self-Organizing Map (SOM)%plotsom     Plot a Self-Organizing Map in 2D%%Classifier combiners%--------------------%averagec    Combining linear classifiers by averaging coefficients%baggingc    Bootstrapping and aggregation of classifiers%rsscc       Random subspace combining classifier%votec       Voting classifier combiner%wvotec      Weighted voting classifier combiner%maxc        Maximum classifier combiner%minc        Minimum classifier combiner%meanc       Mean classifier combiner%medianc     Median classifier combiner%prodc       Product classifier combiner%traincc     Train combining classifier%fixedcc     Fixed combiner construction, back end%parsc       Parse classifier or map%rejectc     Creates reject version of exisiting classifier%parallel    Parallel combining of classifiers%stacked     Stacked combining of classifiers%sequential  Sequential combining of classifiers%%%Regression%----------%linearr     Linear regression%ridger      Ridge regression%lassor      LASSO%svmr        Support vector regression%ksmoothr    Kernel smoother%knnr        k-nearest neighbor regression%pinvr       Pseudo-inverse regression%plsr        Partial least squares regression%plsm        Partial least squares mapping%%testr       Mean squared regression error%rsquared    R^2-statistic%%Handling images in datasets and datafiles%-----------------------------------------%data2im     Convert dataset to image%getobjsize  Retrieve image size of feature images in datasets%getfeatsize Retrieve image size of object images in datasets%obj2feat    Transform object images to feature images in dataset%feat2obj    Transform feature images to object images in dataset%im2feat     Convert image to feature in dataset%im2obj      Convert image to object in dataset%selectim    Select image in multi-band object image dataset/datafile%show        Display objects in datasets, datafiles and mappings%%Operations on images in datasets and datafiles%----------------------------------------------%classim     Classify image using a given classifier%dataim      Image operation on dataset images (features or objects)%doublem     Convert datafile images into double%filtim      Image operation on objects in datafiles/datasets%datfilt     Filter dataset image (outdated)%datgauss    Filter dataset image by Gaussian filter%datunif     Filter dataset image by uniform filter%hsv2rgb     Convert HSV to RGB images%rgb2hsv     Convert RGB to HSV images%spatm       Augment image dataset with spatial label information%im_bdilation      Binary dilation%im_berosion       Binary erosion%im_box            Bounding box%im_bpropagation   Binary propagation%im_center         Center image%im_fft            FFT transform (and more)%im_gaussf         Gaussian filtering%im_gray           Multi-band to gray-value conversion%im_hist_equalize  Histogram equalization%im_invert         Invert image%im_label          Labeling binary images%im_maxf           Maximum filter%im_minf           Minimum filter%im_resize         Resize images%im_rotate         Rotate images%im_scale          Scale iamges%im_select_blob    Select largest blob%im_stretch        Contrast stretching of images%im_threshold      Threshold images%%Feature extraction from images in datasets and datafiles%--------------------------------------------------------%histm       Convert images to histograms%im_moments  Computes moments as features from object images%im_mean     Computes center of gravity%im_measure  Computes some measurements%im_profile  Computes image profiles%im_stat     Compute some simple statistics%%Clustering and distances%------------------------%distm       Distance matrix between two data sets.%emclust     Expectation - maximization clustering%proxm       Proximity mapping and kernel construction%hclust      Hierarchical clustering%kcentres    k-centres clustering%kmeans      k-means clustering%modeseek    Clustering by modeseeking%%mds         Non-linear mapping by multi-dimensional scaling (Sammon)%mds_cs      Linear mapping by classical scaling%mds_init    Initialisation of multi-dimensional scaling%mds_stress  Dissimilarity of distance matrices%%Plotting%--------%gridsize    Set gridsize used in the PRTools plot commands%plotc       Plot discriminant function for two features%plote       Plot error curves%plotf       Plot feature distribution%plotm       Plot mapping%ploto       Plot object functions%plotr       Plot regression functions%plotdg      Plot dendrgram (see hclust)%scatterd    Scatterplot%scatterdui  Scatterplot scatterplot with feature selection%scatterr    Scatter regression dataset%%Various tests and support routines%----------------------------------%cdats       Support routine for checking datasets%iscolumn    Test on column array%iscomdset   Test on compatible datasets%isdataim    Test on image dataset%isdataset   Test on dataset%isfeatim    Test on feature image dataset%ismapping   Test on mapping%isobjim     Test on object image dataset%isparallel  Test on parallel mapping%isstacked   Test on stacked mapping%issym.m     Test on symmetric matrix%isvaldset   Test on valid dataset%isvaldfile  Test on valid datafile%matchlablist Match entries of label lists%newfig      Control of figures on the screen%newline     Generate a new line in the command window%labcmp      Compare two label lists and find the differences%nlabcmp     Compare two label lists and count the differences%testdatasize Check datasize and convert datafile to dataset%%Examples%--------%prex_cleval     learning curves%prex_combining  classifier combining%prex_confmat    confusion matrix, scatterplot and gridsize%prex_datafile   datafile usage%prex_datasets   standard datasets%prex_density    Various density plots%prex_eigenfaces Use of images and eigenfaces%prex_matchlab   K-means clustering and matching labels%prex_mcplot     Multi-class classifier plot%prex_plotc      Dataset scatter and classifier plot%prex_som        Training a SelfOrganizing Maps%prex_spatm      Spatial smoothing of image classification%prex_cost       Cost matrices and rejection%prex_logdens    Density based classifier improvement%prex_regr       Regression example%%prversion   returns version information on PRTools%prprogress  report progress control%prwarning   control PRTools warning level%prmemory    controol PRTools large dataset handling%prtver      prtools version back end%typp        list prtools routine nicely% Copyright: R.P.W. Duin, r.p.w.duin@prtools.org% Faculty EWI, Delft University of Technology% P.O. Box 5031, 2600 GA Delft, The Netherlands