BayesClassification {AdaptGauss}

BayesClassification

Description

Bayes Klassifikation den Daten zuordnen

Usage

BayesClassification(Data, Means, SDs, Weights, IsLogDistribution = Means
  * 0, ClassLabels = c(1:length(Means)))

Arguments

Data

vector of Data

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

ClassLabels

Optional numbered class labels that are assigned to the classes. default (1:L), L number of different components of gaussian mixture model

Value

Cls(1:n,1:d) classiffication of Data, such that 1= first component of gaussian mixture model, 2= second component of gaussian mixture model and so on. For Every datapoint a number is returned.

Author(s)

Michael Thrun