Developer Guide for Intel® Data Analytics Acceleration Library 2016 Update 4
Naïve Bayes classifier in the batch processing mode follows the general workflow described in Usage Model: Training and Prediction.
For a description of the input and output, refer to Usage Model: Training and Prediction.
At the training stage, Naïve Bayes classifier has the following parameters:
|
Parameter |
Default Value |
Description |
|
|---|---|---|---|
|
algorithmFPType |
double |
The floating-point type that the algorithm uses for intermediate computations. Can be float or double. |
|
|
method |
defaultDense |
Available computation methods for the Naïve Bayes classifier:
|
|
|
nClasses |
Not applicable |
The number of classes, a required parameter. |
|
|
priorClassEstimates |
1/nClasses |
Vector of size nClasses that contains prior class estimates. The default value applies to each vector element. |
|
|
alpha |
1 |
Vector of size p that contains the imagined occurrences of features. The default value applies to each vector element. |
|
For a description of the input and output, refer to Usage Model: Training and Prediction.
At the prediction stage, Naïve Bayes classifier has the following parameters:
|
Parameter |
Default Value |
Description |
|
|---|---|---|---|
|
algorithmFPType |
double |
The floating-point type that the algorithm uses for intermediate computations. Can be float or double. |
|
|
method |
defaultDense |
Performance-oriented computation method, the only method supported by the algorithm. |
|
|
nClasses |
Not applicable |
The number of classes, a required parameter. |
|