Logistic Loss#

LogisticLoss is a common objective function used for binary classification.


Computational methods



Mathematical formulation#

Refer to Developer Guide: Logistic Loss.

Programming Interface#

All types and functions in this section are declared in the oneapi::dal::logloss_objective namespace.


template<typename Float = float, typename Method = method::by_default, typename Task = task::by_default>
class descriptor#
Template Parameters
  • Float – The floating-point type that the algorithm uses for intermediate computations. Can be float or double.

  • Method – Tag-type that specifies an implementation of algorithm. Can be method::dense_batch.

  • Task – Tag-type that specifies the type of the problem to solve. Can be task::compute.


descriptor(double l1_regularization_coefficient = 0.0, double l2_regularization_coefficient = 0.0, bool fit_intercept = true)#

Creates a new instance of the class with the given l1_regularization_coefficient, l2_regularization_coefficient and fit_intercept property values.


double l1_regularization_coefficient#

The L1-regularization strength.

Getter & Setter
double get_l1_regularization_coefficient() const
auto & set_l1_regularization_coefficient(double value)
bool intercept_flag#

The fit_intercept flag.

Getter & Setter
bool get_intercept_flag() const
auto & set_intercept_flag(bool fit_intercept)
double l2_regularization_coefficient#

The L2-regularization strength.

Getter & Setter
double get_l2_regularization_coefficient() const
auto & set_l2_regularization_coefficient(double value)

Method tags#

struct dense_batch#
using by_default = dense_batch#

Task tags#

struct compute#
using by_default = compute#