Provides methods to run implementations of the model-based prediction.
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- Parameters
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fptype | Data type to use in intermediate computations for model-based prediction in the batch processing mode, double or float |
method | Computation method in the batch processing mode, Method |
- Enumerations
- Method Computation methods for model-based prediction
- References
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- Aliases
Batch_Float64DefaultDense
is an alias of Batch(fptype=float64, method=daal.algorithms.gbt.regression.prediction.defaultDense)
Batch_Float32DefaultDense
is an alias of Batch(fptype=float32, method=daal.algorithms.gbt.regression.prediction.defaultDense)
def __init__ |
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- Variant 1
- Default constructor
- Variant 2
Constructs a gradient boosted trees prediction algorithm by copying input objects and parameters of another gradient boosted trees prediction algorithm
- Parameters
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other | Algorithm to use as the source to initialize the input objects and parameters of the algorithm |
Returns a pointer to a newly allocated gradient boosted trees prediction algorithm with a copy of the input objects for this gradient boosted trees prediction algorithm
- Returns
- Pointer to the newly allocated algorithm
Get input objects for the algorithm
- Returns
- input objects of the algorithm
Returns the method of the algorithm
- Returns
- Method of the algorithm
Returns the structure that contains the result of model-based prediction
- Returns
- Structure that contains the result of the model-based prediction
def parameter |
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- Variant 1
Gets parameter of the algorithm
- Returns
- parameter of the algorithm
- Variant 2
Gets parameter of the algorithm
- Returns
- parameter of the algorithm
The documentation for this class was generated from the following file:
- gbt/regression/prediction.py