Contents

PURPOSE ^

CLASSIFY

SYNOPSIS ^

This is a script file.

DESCRIPTION ^

 CLASSIFY
 See also

 Clustering:
   demoCluster        - Clustering demo.
   demoGenData        - Generate data drawn form a mixture of Gaussians.
   kmeans2            - Fast version of kmeans clustering.
   meanShift          - meanShift clustering algorithm.
   meanShiftIm        - Applies the meanShift algorithm to a joint spatial/range image.
   meanShiftImExplore - Visualization to help choose sigmas for meanShiftIm.

 Calculating distances efficiently:
   distMatrixShow     - Useful visualization of a distance matrix of clustered points.
   softMin            - Calculates the softMin of a vector.
   pdist2             - Calculates the distance between sets of vectors.

 Principal components analysis:
   pca                - Principal components analysis (alternative to princomp).
   pcaApply           - Companion function to pca.
   pcaRandVec         - Generate random vectors in PCA subspace.
   pcaVisualize       - Visualization of quality of approximation of X given principal comp.
   visualizeData      - Project high dim. data unto principal components (PCA) for visualization.

 Classification methods with a common interface:
   demoClassify       - A demo used to test and demonstrate the usage of classifiers (clf*)
   nfoldxval          - Runs n-fold cross validation on data with a given classifier.
   confMatrix         - Generates a confusion matrix according to true and predicted data labels.
   confMatrixShow     - Used to display a confusion matrix.
   clfDecTree         - Wrapper for treefit that makes decision trees compatible with nfoldxval.
   clfDecTreeFwd      - Apply the decision tree to data X.
   clfDecTreeTrain    - Train a decision tree classifier.
   clfEcoc            - Wrapper for ecoc that makes ecoc compatible with nfoldxval.
   clfEcocCode        - Generates optimal ECOC codes when 3<=nclasses<=7.
   clfKnn             - Create a k nearest neighbor classifier.
   clfKnnDist         - k-nearest neighbor classifier based on a distance matrix D.
   clfKnnFwd          - Apply a k-nearest neighbor classifier to X.
   clfKnnTrain        - Train a k nearest neighbor classifier (memorization).
   clfLda             - Create a Linear Discriminant Analysis (LDA) classifier.
   clfLdaFwd          - Apply the Linear Discriminant Analysis (LDA) classifier to data X.
   clfLdaTrain        - Train a Linear Discriminant Analysis (LDA) classifier.
   clfSvm             - Wrapper for svm that makes svm compatible with nfoldxval.

 Radial Basis Functions (RBFs)
   rbfComputeBasis    - Get locations and sizes of radial basis functions for use in rbf network.
   rbfComputeFtrs     - Evaluate features of X given a set of radial basis functions.
   rbfDemo            - Demonstration of rbf networks for regression.

CROSS-REFERENCE INFORMATION ^

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