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Contents

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.

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Implicit Alternating Least Squares

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Distributed Processing