Provides methods to access the result obtained with the compute() method of decision forest model-based training.
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def __init__ |
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args |
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def allocate_{Float64|Float32} |
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input, |
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parameter, |
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method |
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Allocates memory to store the result of decision forest model-based training
- Parameters
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input | Pointer to an object containing the input data |
method | Computation method for the algorithm |
parameter | Parameter of decision forest model-based training |
- Returns
- Status of allocation
- Full Names
allocate_Float64
is for float64
allocate_Float32
is for float32
def check |
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self, |
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input, |
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par, |
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method |
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Checks the result of decision forest model-based training
- Parameters
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input | Input object for the algorithm |
par | Parameter of the algorithm |
method | Computation method |
- Returns
- Status of checking
Returns the result of decision forest model-based training
- Parameters
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id | Identifier of the result |
- Returns
- Result that corresponds to the given identifier
def getEngine |
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id |
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Returns the engine updated after computations
- Parameters
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id | Identifier of the result |
- Returns
- Result that corresponds to the given identifier
def getSerializationTag |
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self | ) |
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getSerializationTag(Result self) -> int
def getTable |
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id |
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Returns the result of decision forest model-based training
- Parameters
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id | Identifier of the result |
- Returns
- Result that corresponds to the given identifier
impl(Result self) -> daal.algorithms.decision_forest.regression.training.Result.ResultImpl *
def set |
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id, |
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value |
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Sets the result of decision forest model-based training
- Parameters
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id | Identifier of the result |
value | Result |
def setTable |
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self, |
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id, |
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value |
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Sets the result of decision forest model-based training
- Parameters
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id | Identifier of the result |
value | Result |
The documentation for this class was generated from the following file:
- decision_forest/regression/training.py