Batch Processing¶

Input¶

Initialization of item factors for the implicit ALS algorithm accepts the input described below. Pass the Input ID as a parameter to the methods that provide input for your algorithm. For more details, see Algorithms.

Input for Implicit Alternating Least Squares Initialization (Batch Processing)

Input ID

Input

data

Pointer to the $$m \times n$$ numeric table with the mining data.

The input can be an object of any class derived from NumericTable except PackedTriangularMatrix and PackedSymmetricMatrix.

Parameters¶

Initialization of item factors for the implicit ALS algorithm has the following parameters:

Parameters for Implicit Alternating Least Squares Initialization (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

$$10$$

The total number of factors.

engine

SharePtr< engines:: mt19937:: Batch>()

Pointer to the random number generator engine that is used internally at the initialization step.

Output¶

Initialization of item factors for the implicit ALS algorithm calculates the result described below. Pass the Result ID as a parameter to the methods that access the results of your algorithm. For more details, see Algorithms.

Output for Implicit Alternating Least Squares Initialization (Batch Processing)

Result ID

Result

model

The model with initialized item factors. The result can only be an object of the Model class.