RegularizationType enum

Regularization types

Machine learning linear models are prone to overfitting, or, in other words, they may lose generalization ability in their learning process: overfitted models show quite high quality on training data, but in the same time they perform very badly on previously unseen data.

The main reason of that is uncontrolled growth of linear model coefficients. To avoid this, it is needed to measure a magnitude of coefficients vector and consider it during the model's learning.

Inheritance

• Object
• Enum
• RegularizationType

Constructors

RegularizationType()

const

Values

L1 → const RegularizationType

uses Manhattan norm of a vector to calculate magnitude of learned coefficients. Applicable for LinearOptimizerType.coordinate

L2 → const RegularizationType

uses Euclidean norm of a vector to calculate magnitude of learned coefficients. Applicable for LinearOptimizerType.gradient

Properties

hashCode → int

The hash code for this object.

no setter, inherited

index → int

A numeric identifier for the enumerated value.

no setter, inherited

runtimeType → Type

A representation of the runtime type of the object.

no setter, inherited

Methods

noSuchMethod(Invocation invocation) → dynamic

Invoked when a nonexistent method or property is accessed.

inherited

toString() → String

A string representation of this object.

inherited

Operators

operator ==(Object other) → bool

The equality operator.

inherited

Constants

values → const List<RegularizationType>

A constant List of the values in this enum, in order of their declaration.