Contains classes for Decision forest models training.
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| struct | Parameter |
| | Decision forest algorithm parameters. More...
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| class | Result |
| | Provides methods to access final results obtained with the compute() method of the LogitBoost training algorithm in the batch processing mode. More...
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| Enumerator |
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| defaultDense |
Bagging, random choice of features, Gini impurity
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| enum ResultNumericTableId |
| Enumerator |
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| outOfBagError |
Numeric table 1x1 containing out-of-bag erro. 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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