# Logistic Loss#

LogisticLoss is a common objective function used for binary classification.

 Operation Computational methods dense_batch dense_batch

## 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.

### Descriptor#

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.

Constructors

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.

Properties

double l1_regularization_coefficient#

The L1-regularization strength.

Getter & Setter
`double get_l1_regularization_coefficient() const`
`auto & set_l1_regularization_coefficient(double value)`
Invariants
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)`
Invariants

#### Method tags#

struct dense_batch#
using by_default = dense_batch#