C++ API Reference for Intel® Data Analytics Acceleration Library 2018 Update 3

References | Namespaces | Classes | Enumerations

Contains a class for model-based training. More...

References

 Batch
 

Namespaces

 daal::algorithms::gbt::regression::training
 Contains a class for model-based training.
 
 daal::algorithms::gbt::regression::training::interface1
 Contains version 1.0 of the Intel(R) Data Analytics Acceleration Library (Intel(R) DAAL) interface.
 

Classes

class  Parameter
 Parameters for the gradient boosted trees algorithm. More...
 
class  Input
 Input objects for model-based training More...
 
class  Result
 Provides methods to access the result obtained with the compute() method of model-based training. More...
 

Enumerations

enum  Method { xboost = 0, defaultDense = 0 }
 Computation methods for gradient boosted trees classification model-based training. More...
 
enum  LossFunctionType
 Loss function type. More...
 
enum  InputId { data = algorithms::regression::training::data, dependentVariable = algorithms::regression::training::dependentVariables }
 Available identifiers of input objects for model-based training. More...
 
enum  ResultId { model = algorithms::regression::training::model }
 Available identifiers of the result of model-based training. More...
 

Enumeration Type Documentation

enum InputId

Enumerator
data 

Input data table

dependentVariable 

Values of the dependent variable for the input data

enum LossFunctionType

enum Method

Enumerator
xboost 

Extreme boosting (second-order approximation of objective function, regularization on number of leaves and their weights), Chen et al.

defaultDense 

Default training method

enum ResultId

Enumerator
model 

model

For more complete information about compiler optimizations, see our Optimization Notice.