Provides methods for linear regression model-based training in the online processing mode.
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template<typename algorithmFPType = DAAL_ALGORITHM_FP_TYPE, Method method = normEqDense>
class daal::algorithms::linear_regression::training::interface1::Online< algorithmFPType, method >
- Template Parameters
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algorithmFPType | Data type to use in intermediate computations for linear regression model-based training , double or float |
method | Linear regression training method, Method |
- Enumerations
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- References
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◆ Online() [1/2]
◆ Online() [2/2]
Constructs a linear regression training algorithm by copying input objects and parameters of another linear regression training algorithm in the online 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 |
◆ clone()
Returns a pointer to a newly allocated linear regression training algorithm with a copy of the input objects and parameters of this linear regression training algorithm in the online processing mode
- Returns
- Pointer to the newly allocated algorithm
◆ getMethod()
virtual int getMethod |
( |
| ) |
const |
|
inlinevirtual |
Returns the method of the algorithm
- Returns
- Method of the algorithm
Implements AlgorithmIface.
◆ getPartialResult()
Returns the structure that contains a partial result of linear regression model-based training
- Returns
- Structure that contains a partial result of linear regression model-based training
◆ getResult()
Returns the structure that contains the result of linear regression model-based training
- Returns
- Structure that contains the result of linear regression model-based training
◆ input
◆ parameter
The documentation for this class was generated from the following file: