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.
   pdist2             - Calculates the distance between sets of vectors.
   softMin            - Calculates the softMin of a vector.

 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.

 Confusion matrix display.
   confMatrix         - Generates a confusion matrix according to true and predicted data labels.
   confMatrixShow     - Used to display a confusion matrix.

 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.

 Fast random fern classification/regression code.
   fernsClfApply      - Apply learned fern classifier.
   fernsClfTrain      - Train random fern classifier.
   fernsInds          - Compute indices for each input by each fern.
   fernsRegApply      - Apply learned fern regressor.
   fernsRegTrain      - Train boosted fern regressor.

CROSS-REFERENCE INFORMATION ^

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