a | PageHinckleyAlpha: The alpha value to use in the Page Hinckley change detection tests. | default: 0.005 |
b | binarySplits: Only allow binary splits. | default: false |
c | splitConfidence: The allowable error in split decision, values closer to 0 will take longer to decide. | default: 1.0E-7 |
d | nominalEstimator: Nominal estimator to use. | default: NominalAttributeClassObserver |
e | memoryEstimatePeriod: How many instances between memory consumption checks. | default: 1000000 |
f | AlternateTreeFadingFactor: The fading factor to use when deciding if an alternate tree should replace an original. | default: 0.995 |
g | gracePeriod: The number of instances a leaf should observe between split attempts. | default: 200 |
h | PageHinckleyThreshold: The threshold value to be used in the Page Hinckley change detection tests. | default: 50 |
j | learningRatio_Decay_or_Const: learning Ratio Decay or const parameter. | default: false |
l | leafprediction: Leaf prediction to use. | default: NBAdaptive |
m | maxByteSize: Maximum memory consumed by the tree. | default: 33554432 |
n | numericEstimator: Numeric estimator to use. | default: FIMTDDNumericAttributeClassObserver |
p | noPrePrune: Disable pre-pruning. | default: false |
q | nbThreshold: The number of instances a leaf should observe before permitting Naive Bayes. | default: 0 |
r | removePoorAtts: Disable poor attributes. | default: false |
s | splitCriterion: Split criterion to use. | default: SDRSplitCriterion |
t | tieThreshold: Threshold below which a split will be forced to break ties. | default: 0.05 |
u | AlternateTreeTime: The 'time' (in terms of number of instances) value to use when deciding if an alternate tree should be discarded. | default: 1500 |
w | learningRatio: Learning ratio to use for training the Perceptrons in the leaves. | default: 0.01 |
y | AlternateTreeTMin: The Tmin value to use when deciding if an alternate tree should replace an original. | default: 150 |
z | stopMemManagement: Stop growing as soon as memory limit is hit. | default: false |