|  | ## Subgroup Discovery (Meta)

#### Synopsis

A Subgroup Discovery meta learning scheme

#### Description

Subgroup discovery learner.

#### Input

- training set: expects: ExampleSet

#### Output

- model:

#### Parameters

- iterations: The maximum number of iterations.
- ratio internal bootstrap: Fraction of examples used for training (internal bootstrapping). If activated (value < 1) only the rest is used to estimate the biases.
- ROC convex hull filter: A parameter whether to discard all rules not lying on the convex hull in ROC space.
- additive reweight: If enabled then resampling is done by additive reweighting, otherwise by multiplicative reweighting.
- gamma: Factor used for multiplicative reweighting. Has no effect in case of additive reweighting.
- use local random seed: Indicates if a local random seed should be used.
- local random seed: Specifies the local random seed

#### ExampleProcess