BayesDecisionBoundaries {AdaptGauss} | R Documentation |
Function finds the intersections of Gaussians or LogNormals
BayesDecisionBoundaries(Means,SDs,Weights,IsLogDistribution,MinData,MaxData,Ycoor)
Means |
vector[1:L] of Means of Gaussians (of GMM) |
SDs |
vector of standard deviations, estimated Gaussian Kernels, has to be the same length as Means |
Weights |
vector of relative number of points in Gaussians (prior probabilities), has to be the same length as Means |
IsLogDistribution |
Optional, ==1 if distribution(i) is a LogNormal, default vector of zeros of length 1:L |
MinData |
Optional, Beginning of range, where the Boundaries are searched for, default min(M) |
MaxData |
Optional, End of range, where the Boundaries are searched for, default max(M) |
Ycoor |
Optional, Bool, if TRUE instead of vector of DecisionBoundaries list of DecisionBoundaries and DBY is returned |
DecisionBoundaries |
vector[1:L-1], Bayes decision boundaries |
DBY |
if (Ycoor==TRUE), y values at the cross points of the Gaussians is also returned, that the return is a list of DecisionBoundaries and DBY |
Michael Thrun, Rabea Griese
Duda, R. O., Hart, P. E., & Stork, D. G. (2001). Pattern classification. 2nd. Edition. New York, p. 512ff
AdaptGauss
,Intersect2Mixtures
,Bayes4Mixtures