Contains a class for decision forest model-based training.
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| class | Parameter |
| | Parameters for the decision forest algorithm. More...
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| class | Input |
| | Input objects for decision forest model-based training More...
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| class | Result |
| | Provides methods to access the result obtained with the compute() method of decision forest model-based training. More...
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| Enumerator |
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| data |
Input data table
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| dependentVariable |
Values of the dependent variable for the input data
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| Enumerator |
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| defaultDense |
Bagging, random choice of features, variance-based impurity
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| Enumerator |
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| model |
decision forest model
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| enum ResultNumericTableId |
| Enumerator |
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| outOfBagError |
Numeric table 1x1 containing out-of-bag error. Computed when computeOutOfBagError option is on
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| variableImportance |
Numeric table 1x(number of features) containing variable importance value. Computed when parameter.varImportance != none
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| outOfBagErrorPerObservation |
Numeric table 1x(number of observations) containing out-of-bag error value computed. Computed when computeOutOfBagErrorPerObservation option is on
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