Batch Processing

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.