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Code covered by the BSD License

example3parameters(X, y, Xval... Initialization
gaussianKernel(x1, x2, sigma) RBFKERNEL returns a radial basis function kernel between x1 and x2
linearKernel(x1, x2) LINEARKERNEL returns a linear kernel between x1 and x2
plotData(X, y) PLOTDATA Plots the data points X and y into a new figure
svmPredict(model, X) SVMPREDICT returns a vector of predictions using a trained SVM model
svmTrain(X, Y, C, kernelFunct... SVMTRAIN Trains an SVM classifier using a simplified version of the SMO
visualizeBoundary(X, y, model... VISUALIZEBOUNDARY plots a non-linear decision boundary learned by the SVM
visualizeBoundaryLinear(X, y,... VISUALIZEBOUNDARYLINEAR plots a linear decision boundary learned by the
DecisionBoundary_SVMs.m
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Decision Boundary using SVMs

31 Jan 2012

Decision Boundary Via Support Vector machines (SVMs)

File Information
Description	This code will find out the decision boundary of 2D data-set. file contains multiple supporting functions and main program is DecisionBoundary_SVMs.m The examples sets are contains linear and non-linear data-set and using SVMs with RGF kernel we will find out the decision boundary of data-set.
Required Products	MATLAB
MATLAB release	MATLAB 7.12 (2011a)
Other requirements	Knowledge of Support Vector Machines.

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Everyone's Tags	decision boundary, gaussian kernel, gui, linear data set, linear svm, mathematics, nonlinear data set, nonlinear svm, optimization, rbf kernel, support vectors machine, svms(2)
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