Provides methods for linear regression model-based training in the batch processing mode.
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- Parameters
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fptype | Data type to use in intermediate computations for linear regression model-based training, double or float |
method | Linear regression training method, Method |
- Enumerations
- Method Computation methods
- References
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- Aliases
Batch_Float64QrDense
is an alias of Batch(fptype=float64, method=daal.algorithms.linear_regression.training.qrDense)
Batch_Float64NormEqDense
is an alias of Batch(fptype=float64, method=daal.algorithms.linear_regression.training.normEqDense)
Batch_Float32QrDense
is an alias of Batch(fptype=float32, method=daal.algorithms.linear_regression.training.qrDense)
Batch_Float32NormEqDense
is an alias of Batch(fptype=float32, method=daal.algorithms.linear_regression.training.normEqDense)
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- Variant 1
- Default constructor
- Variant 2
Constructs a linear regression training algorithm by copying input objects and parameters of another linear regression training algorithm in the batch processing mode
- 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 linear regression training algorithm with a copy of the input objects and parameters for this linear regression training algorithm in the batch processing mode
- Returns
- Pointer to the newly allocated algorithm
getInput(Batch self) -> Input
Returns the method of the algorithm
- Returns
- Method of the algorithm
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
Resets the results of linear regression model-based training
The documentation for this class was generated from the following file:
- linear_regression/training.py