Visibility: public Uploaded 19-04-2018 by Tim Beurskens RapidMiner_8.1.001 1 runs
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A RapidMiner Flow


RandomForest__apply_prepruningActivates the pre pruning and delivers a prepruned tree.default: true
RandomForest__apply_pruningActivates the pruning of the tree.default: true
RandomForest__confidenceThe confidence level used for the pessimistic error calculation of pruning.default: 0.25
RandomForest__criterionSpecifies the used criterion for selecting attributes and numerical splits.default: gain_ratio
RandomForest__enable_parallel_executionThis parameter enables the parallel execution of this operator. Please disable the parallel execution if you run into memory problems.default: true
RandomForest__guess_subset_ratioIndicates that log(m) + 1 features are used, otherwise a ratio has to be specified.default: true
RandomForest__local_random_seedSpecifies the local random seeddefault: 1992
RandomForest__maximal_depthThe maximum tree depth (-1: no bound)default: 20
RandomForest__minimal_gainThe minimal gain which must be achieved in order to produce a split.default: 0.1
RandomForest__minimal_leaf_sizeThe minimal size of all leaves.default: 2
RandomForest__minimal_size_for_splitThe minimal size of a node in order to allow a split.default: 4
RandomForest__number_of_prepruning_alternativesThe number of alternative nodes tried when prepruning would prevent a split.default: 3
RandomForest__number_of_treesThe number of learned random trees.default: 10
RandomForest__random_splitsSplit numerical attributes randomly.default: false
RandomForest__subset_ratioRatio of randomly chosen attributes to testdefault: 0.2
RandomForest__use_local_random_seedIndicates if a local random seed should be used.default: false
RandomForest__voting_strategyVoting strategy used to determine prediction.default: confidence vote


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