ClassifyByDecisionBoundaries: Classify Data according to decision Boundaries

In AdaptGauss: Gaussian Mixture Models (GMM)

Description

The Decision Boundaries calculated through Bayes Theorem.

Usage

ClassifyByDecisionBoundaries(Data,DecisionBoundaries,ClassLabels)

Arguments

Data	vector of Data
DecisionBoundaries	decision boundaries, BayesDecisionBoundaries
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

References

Duda, R. O., Hart, P. E., & Stork, D. G. (2001). Pattern classification. 2nd. Edition. New York, p. 512ff

See Also

BayesDecisionBoundaries, Bayes4Mixtures

AdaptGauss documentation built on March 26, 2020, 7:57 p.m.