ClassifyByDecisionBoundaries {AdaptGauss} | R Documentation |

## Classify Data according to decision Boundaries

### Description

The Decision Boundaries calculated through Bayes Theorem.

### Usage

```
ClassifyByDecisionBoundaries(Data,DecisionBoundaries,ClassLabels)
```

### Arguments

`Data` |
vector of Data |

`DecisionBoundaries` |
decision boundaries, |

`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`

[Package

*AdaptGauss*version 1.6 Index]