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Subgroup Discovery (Meta) (AI Studio Core)

Synopsis

A Subgroup Discovery meta learning scheme

Description

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