4801 1 moa.HoeffdingAdaptiveTree 2 Moa__16.04_April_2016_1.0 Moa implementation of HoeffdingAdaptiveTree 2016-10-05T19:31:54 English Moa__16.04_April_2016 b flag false binarySplits: Only allow binary splits. c option 1.0E-7 splitConfidence: The allowable error in split decision, values closer to 0 will take longer to decide. d baselearner NominalAttributeClassObserver nominalEstimator: Nominal estimator to use. e option 1000000 memoryEstimatePeriod: How many instances between memory consumption checks. g option 200 gracePeriod: The number of instances a leaf should observe between split attempts. l option NBAdaptive leafprediction: Leaf prediction to use. m option 33554432 maxByteSize: Maximum memory consumed by the tree. n baselearner GaussianNumericAttributeClassObserver numericEstimator: Numeric estimator to use. p flag false noPrePrune: Disable pre-pruning. q option 0 nbThreshold: The number of instances a leaf should observe before permitting Naive Bayes. r flag false removePoorAtts: Disable poor attributes. s baselearner InfoGainSplitCriterion splitCriterion: Split criterion to use. t option 0.05 tieThreshold: Threshold below which a split will be forced to break ties. z flag false stopMemManagement: Stop growing as soon as memory limit is hit. Verified_Supervised_Data_Stream_Classification