Batch Processing

Training

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

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 Usage Model: Training and Prediction.

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.

For more complete information about compiler optimizations, see our Optimization Notice.
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