|  | ## Weight by Relief

#### Synopsis

Relief measures the relevance of features by sampling examples and comparing the value of the current feature for the nearest example of the same and of a different class.

#### Description

Relief measures the relevance of features by sampling examples and comparing the value of the current feature for the nearest example of the same and of a different class. This version also works for multiple classes and regression data sets. The resulting weights are normalized into the interval between 0 and 1.

#### Input

- example set: expects: ExampleSet

#### Output

- weights:
- example set:

#### Parameters

- normalize weights: Activates the normalization of all weights.
- number of neighbors: Number of nearest neigbors for relevance calculation.
- sample ratio: Number of examples used for determining the weights.
- use local random seed: Indicates if a local random seed should be used.
- local random seed: Specifies the local random seed

#### ExampleProcess