|  | ## Weight by SVM

#### Synopsis

This operator uses the coefficients of a hyperplance calculated by an SVM as feature weights.

#### Description

Uses the coefficients of the normal vector of a linear SVM as feature weights. In contrast to most of the SVM based operators available in RapidMiner, this one works for multiple classes, too. Please note that the attribute values, however, still have to be numerical. Please use appropriate preprocessing operators in order to ensure this.

#### Input

- example set: expects: ExampleSet

#### Output

- weights:
- example set:

#### Parameters

- normalize weights: Activates the normalization of all weights.
- C: The SVM complexity weighting factor.

#### ExampleProcess