Subgroup Discovery (Meta) (AI Studio Core)
Synopsis
A Subgroup Discovery meta learning schemeDescription
Subgroup discovery learner.
Input
- training set (IOObject)
Output
- model (IOObject)
Parameters
- iterationsThe maximum number of iterations.
- ratio internal bootstrapFraction of examples used for training (internal bootstrapping). If activated (value < 1) only the rest is used to estimate the biases.
- ROC convex hull filterA parameter whether to discard all rules not lying on the convex hull in ROC space.
- additive reweightIf enabled then resampling is done by additive reweighting, otherwise by multiplicative reweighting.
- gammaFactor used for multiplicative reweighting. Has no effect in case of additive reweighting.
- use local random seedIndicates if a local random seed should be used.
- local random seedSpecifies the local random seed