Provides methods to access the result obtained with the compute() method of linear regression model-based training.
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| def allocate_{Float64|Float32} |
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- Variant 1
Allocates memory to store the result of linear regression 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 linear regression model-based training |
- Returns
- Status of computations
- Variant 2
Allocates memory to store the result of linear regression model-based training
- Parameters
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| partialResult | Pointer to an object containing the input data |
| method | Computation method of the algorithm |
| parameter | Parameter of linear regression model-based training |
- Returns
- Status of computations
- Full Names
allocate_Float64 is for float64
allocate_Float32 is for float32
- Variant 1
Checks the result of linear regression 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 computations
- Variant 2
Checks the result of the linear regression model-based training
- Parameters
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| pr | PartialResult of the algorithm |
| par | Parameter of the algorithm |
| method | Computation method |
- Returns
- Status of computations
Returns the result of linear regression model-based training
- Parameters
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| id | Identifier of the result |
- Returns
- Result that corresponds to the given identifier
| def getSerializationTag |
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getSerializationTag(Result self) -> int
| def set |
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id, |
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value |
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Sets the result of linear regression 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:
- linear_regression/training.py