Skip to main content

Subgroup Discovery (Meta)

Synopsis​

A

Subgroup Discovery meta learning scheme

Description​

Subgroup discovery learner.

Input​

training set​

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