Provides methods to access the result obtained with the compute() method of model-based training.
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- Deprecated:
- This item will be removed in a future release.
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 final results of the logistic regression training algorithm
- Parameters
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input | Input of the logistic regression training algorithm |
parameter | Parameters of the algorithm |
method | logistic regression computation method |
- 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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s Checks the result of 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 model trained with the logistic regression algorithm
- Parameters
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id | Identifier of the result, classifier.training.ResultId |
- Returns
- Model trained with the logistic regression algorithm
def getSerializationTag |
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self | ) |
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getSerializationTag(Result self) -> int
def set |
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self, |
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id, |
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value |
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Sets the result of 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:
- logistic_regression/training.py