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:

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

\(10\)

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.

Prediction

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:

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.