Developer Guide for Intel® Data Analytics Acceleration Library 2016 Update 4
For a description of the input and output, refer to Usage Model: Training and Prediction.
At the training stage, the implicit ALS recommender 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:
|
|
|
nFactors |
10 |
The total number of factors. |
|
|
maxIterations |
5 |
The number of iterations. |
|
|
alpha |
40 |
The rate of confidence. |
|
|
lambda |
0.01 |
The parameter of the regularization. |
|
|
preferenceThreshold |
0 |
Threshold used to define preference values. 0 is the only threshold supported so far. |
|
For a description of the input and output, refer to Usage Model: Training and Prediction.
At the prediction stage, the implicit ALS recommender 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. |
|