Visibility: public Uploaded 15-07-2016 by Jan van Rijn RapidMiner_6.4.0 0 runs
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A RapidMiner Operator


apply_prepruningActivates the pre pruning and delivers a prepruned tree.default: true
apply_pruningActivates the pruning of the tree.default: true
confidenceThe confidence level used for the pessimistic error calculation of pruning.default: 0.25
criterionSpecifies the used criterion for selecting attributes and numerical splits.default: gain_ratio
guess_subset_ratioIndicates that log(m) + 1 features are used, otherwise a ratio has to be specified.default: true
local_random_seedSpecifies the local random seeddefault: 1992
maximal_depthThe maximum tree depth (-1: no bound)default: 20
minimal_gainThe minimal gain which must be achieved in order to produce a split.default: 0.1
minimal_leaf_sizeThe minimal size of all leaves.default: 2
minimal_size_for_splitThe minimal size of a node in order to allow a split.default: 4
number_of_prepruning_alternativesThe number of alternative nodes tried when prepruning would prevent a split.default: 3
number_of_treesThe number of learned random trees.default: 10
subset_ratioRatio of randomly chosen attributes to testdefault: 0.2
use_local_random_seedIndicates if a local random seed should be used.default: false


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