Provides methods for model-based training in the batch processing mode.
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template<typename algorithmFPType = DAAL_ALGORITHM_FP_TYPE, Method method = defaultDense>
class daal::algorithms::gbt::regression::training::interface1::Batch< algorithmFPType, method >
- Template Parameters
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algorithmFPType | Data type to use in intermediate computations for model-based training, double or float |
method | gradient boosted trees training method, Method |
- Enumerations
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- References
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◆ Batch() [1/2]
◆ Batch() [2/2]
Batch |
( |
const Batch< algorithmFPType, method > & |
other | ) |
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inline |
Constructs a gradient boosted trees training algorithm by copying input objects and parameters of another gradient boosted trees training algorithm in the batch processing mode
- Parameters
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[in] | other | Algorithm to use as the source to initialize the input objects and parameters of the algorithm |
◆ ~Batch()
Destructor
Reimplemented from Batch.
◆ clone()
Returns a pointer to a newly allocated gradient boosted trees training algorithm with a copy of the input objects and parameters for this gradient boosted trees training algorithm in the batch processing mode
- Returns
- Pointer to the newly allocated algorithm
◆ getInput()
Get input objects for the algorithm
- Returns
- input objects of the algorithm
Implements Batch.
◆ getMethod()
virtual int getMethod |
( |
| ) |
const |
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inlinevirtual |
Returns the method of the algorithm
- Returns
- Method of the algorithm
Implements AlgorithmIface.
◆ getResult()
Returns the structure that contains the result of model-based training
- Returns
- Structure that contains the result of model-based training
◆ parameter() [1/2]
Gets parameter of the algorithm
- Returns
- parameter of the algorithm
◆ parameter() [2/2]
Gets parameter of the algorithm
- Returns
- parameter of the algorithm
◆ input
The documentation for this class was generated from the following file: