Algorithm class for training Naive Bayes partial model in the distributed processing mode.
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- Deprecated:
- This item will be removed in a future release.
- Parameters
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fptype | Data type to use in intermediate computations for the multinomial naive Bayes training on the first step in distributed processing mode, double or float |
method | Naive Bayes training method, Method |
- Enumerations
- Method Training methods for the multinomial naive Bayes on the first step in the distributed processing mode
- Aliases
Distributed_Step1LocalFloat64DefaultDense
is an alias of Distributed(step=daal.step1Local, fptype=float64, method=daal.algorithms.multinomial_naive_bayes.training.defaultDense)
Distributed_Step1LocalFloat64FastCSR
is an alias of Distributed(step=daal.step1Local, fptype=float64, method=daal.algorithms.multinomial_naive_bayes.training.fastCSR)
Distributed_Step1LocalFloat32DefaultDense
is an alias of Distributed(step=daal.step1Local, fptype=float32, method=daal.algorithms.multinomial_naive_bayes.training.defaultDense)
Distributed_Step1LocalFloat32FastCSR
is an alias of Distributed(step=daal.step1Local, fptype=float32, method=daal.algorithms.multinomial_naive_bayes.training.fastCSR)
Distributed_Step2MasterFloat64DefaultDense
is an alias of Distributed(step=daal.step2Master, fptype=float64, method=daal.algorithms.multinomial_naive_bayes.training.defaultDense)
Distributed_Step2MasterFloat64FastCSR
is an alias of Distributed(step=daal.step2Master, fptype=float64, method=daal.algorithms.multinomial_naive_bayes.training.fastCSR)
Distributed_Step2MasterFloat32DefaultDense
is an alias of Distributed(step=daal.step2Master, fptype=float32, method=daal.algorithms.multinomial_naive_bayes.training.defaultDense)
Distributed_Step2MasterFloat32FastCSR
is an alias of Distributed(step=daal.step2Master, fptype=float32, method=daal.algorithms.multinomial_naive_bayes.training.fastCSR)
def __init__ |
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- Variant 1
Default constructor
- Parameters
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nClasses | Number of classes |
- Variant 2
Constructs multinomial naive Bayes training algorithm by copying input objects and parameters of another multinomial naive Bayes training algorithm
- Parameters
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other | An algorithm to be used as the source to initialize the input objects and parameters of the algorithm |
Returns a pointer to the newly allocated multinomial naive Bayes training algorithm with a copy of input objects and parameters of this multinomial naive Bayes training algorithm
- Returns
- Pointer to the newly allocated algorithm
Invokes computations and returns partial result
def finalizeCompute |
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self | ) |
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Finalizes computations and returns (final) result
The documentation for this class was generated from the following file:
- multinomial_naive_bayes/training.py