# 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.