|  | ## Cluster Distance Performance

#### Synopsis

Delivers a performance based on cluster centroids.

#### Description

An evaluator for centroid based clustering methods. The average within cluster distance is calculated by averaging the distance between the centroid and all examples of a cluster.

#### Input

- example set: expects: ExampleSet
- cluster model: expects: CentroidClusterModel
- performance: optional: PerformanceVector

#### Output

- performance:
- example set:
- cluster model:

#### Parameters

- main criterion: The main criterion to use
- main criterion only: return the main criterion only
- normalize: divide the criterion by the number of features
- maximize: do not multiply the result by minus one

#### ExampleProcess