Developer Guide for Intel® Data Analytics Acceleration Library 2019 Update 5

Computation

Coordinate Descent algorithm is a special case of an iterative solver. For parameters, input and output of iterative solvers, see Iterative Solver > Computation.

Algorithm parameters

In addition to the input of a iterative solver, Coordinate Descent algorithm accepts 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 method.

engine

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

Pointer to the random number generator engine that is used internally during each iteration to choose a random component of the minimum result vector to be updated.

positive

false

A boolean value. When set to true, it forces the coefficients to be positive.

selection

cyclic

Value that specifies the strategy of certain coordinate selection on each iteration. Except for default ‘cyclic’ value, Coordinate Descent also supports:

‘random’ – on each iteration the index of coordinate is selected randomly by the engine.

skipTheFirstComponents

false

A boolean value. When set to ‘true’, Coordinate Descent algorithm will skip the first component from optimization.

Examples

C++:

Java*:

Python*: