|  | ## Weight by Value Average

#### Synopsis

This operator uses a corpus of examples to characterize a single class by setting feature weights.

#### Description

This operator uses a corpus of examples to characterize a single class by setting feature weights. Characteristic features receive higher weights than less characteristic features. The weight for a feature is determined by calculating the average value of this feature for all examples of the target class. This operator assumes that the feature values characterize the importance of this feature for an example (e.g. TFIDF or others). Therefore, this operator is mainly used on textual data based on TFIDF weighting schemes. To extract such feature values from text collections you can use the Text plugin.

#### Input

- example set: expects: ExampleSet

#### Output

- weights:
- example set:

#### Parameters

- normalize weights: Activates the normalization of all weights.
- class to characterize: The target class for which to find characteristic feature weights.

#### ExampleProcess