Batch Processing

Training

For a description of the input and output, refer to Recommendation Systems Usage Model.

At the training stage, the implicit ALS recommender has the following parameters:

Training Parameters for Implicit Alternating Least Squares Computaion (Batch Processing)
Parameter	Default Value	Description
algorithmFPType	float	The floating-point type that the algorithm uses for intermediate computations. Can be float or double .
method	defaultDense	Available computation methods: defaultDense - performance-oriented method fastCSR - performance-oriented method for CSR numeric tables
nFactors	$LaTex Math image.$	The total number of factors.
maxIterations	$LaTex Math image.$	The number of iterations.
alpha	$LaTex Math image.$	The rate of confidence.
lambda	$LaTex Math image.$	The parameter of the regularization.
preferenceThreshold	$LaTex Math image.$	Threshold used to define preference values. $LaTex Math image.$ is the only threshold supported so far.

For a description of the input and output, refer to Recommendation Systems Usage Model.

At the prediction stage, the implicit ALS recommender has the following parameters:

Prediction Parameters for Implicit Alternating Least Squares Computaion (Batch Processing)
Parameter	Default Value	Description
algorithmFPType	float	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.

In This Topic

Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex.