MATLAB File Help: prtKernelPolynomial
  prtKernelPolynomial  Polynomial kernel object
   kernelObj = prtKernelPolynomial; Generates a kernel object implementing a
   polynomial kernel.  Kernel objects are widely used in several
   prt classifiers, such as prtClassRvm and prtClassSvm.  Polynomial kernels
   implement the following function for 1 x N vectors x1 and x2:
    k(x,y) = (x*y'+c).^d;
   KERNOBJ = prtKernelPolynomial(PROPERTY1, VALUE1, ...) constructs a
   prtKernelPolynomial object KERNOBJ with properties as specified by
   PROPERTY/VALUE pairs. prtKernelPolynomial objects have the following
   user-settable properties:
    d   - Positive scalar value specifying the order of the polynomial.
          (Default value is 2)
    c   - Positive scalar indicating the offset of the polynomial.
          (Default value is 0)
    prtKernelPolynomial objects inherit the TRAIN, RUN, and AND
    methods from prtKernel.
   Polynomial kernels are widely used in the machine
   learning literature. For more information on these kernels, please
   refer to:
   % Example:
    ds = prtDataGenBimodal;         % Load a data set
    k1 = prtKernelPolynomial;       % Create 2 kernels to compare
    k2 = prtKernelPolynomial('d',3);
    k1 = k1.train(ds); % Train
    g1 =;   % Evaluate
    k2 = k2.train(ds); % Train
    g2 =;   % Evaluate
    subplot(2,1,1); imagesc(g1.getObservations);  %Plot the results
    subplot(2,1,2); imagesc(g2.getObservations);
See also
Class Details
Superclasses prtKernel
Sealed false
Construct on load false
Constructor Summary
prtKernelPolynomial Polynomial kernel object 
Property Summary
c Offset 
d Polynomial order 
dataSet The training prtDataSet, only stored if verboseStorage is true.  
dataSetSummary Structure that summarizes prtDataSet. 
isCrossValidateValid False 
isTrained Indicates if prtAction object has been trained. 
name Polynomial Kernel 
nameAbbreviation Poly 
userData User specified data 
verboseStorage Specifies whether or not to store the training prtDataset. 
Method Summary
  and Combine 2 prtKernels into a prtKernelSet 
  get get the object properties 
  optimize Optimize action parameter by exhaustive function maximization. 
  run Run a prtAction object on a prtDataSet object. 
  set set the object properties 
  train Train a prtAction object using training a prtDataSet object.