C++ API Reference for Intel® Data Analytics Acceleration Library 2018 Update 2

Namespaces | Enumerations
daal::algorithms::decision_forest::regression::training Namespace Reference

Contains a class for decision forest model-based training.

Namespaces

 interface1
 Contains version 1.0 of the Intel(R) Data Analytics Acceleration Library (Intel(R) DAAL) interface.
 

Enumerations

enum  Method { defaultDense = 0 }
 Computation methods for decision forest regression model-based training. More...
 
enum  InputId { data = algorithms::regression::training::data, dependentVariable = algorithms::regression::training::dependentVariables }
 Available identifiers of input objects for decision forest model-based training. More...
 
enum  ResultId { model = algorithms::regression::training::model }
 Available identifiers of the result of decision forest model-based training. More...
 
enum  ResultNumericTableId { outOfBagError = lastResultId + 1, variableImportance, outOfBagErrorPerObservation }
 Available identifiers of the result of decision forest model-based training. More...
 

Enumeration Type Documentation

◆ InputId

enum InputId

Enumerator
data 

Input data table

dependentVariable 

Values of the dependent variable for the input data

◆ Method

enum Method

Enumerator
defaultDense 

Bagging, random choice of features, variance-based impurity

◆ ResultId

enum ResultId

Enumerator
model 

decision forest model

◆ ResultNumericTableId

Enumerator
outOfBagError 

Numeric table 1x1 containing out-of-bag error. Computed when computeOutOfBagError option is on

variableImportance 

Numeric table 1x(number of features) containing variable importance value. Computed when parameter.varImportance != none

outOfBagErrorPerObservation 

Numeric table 1x(number of observations) containing out-of-bag error value computed. Computed when computeOutOfBagErrorPerObservation option is on

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