Enum MLAlgorithm 

pub enum MLAlgorithm {
    LinearRegression,
    SVM,
    RandomForest,
    GradientBoosting,
    NeuralNetwork,
    EnsembleMethod,
    DeepRL,
    GraphNN,
}

Advanced machine learning algorithms for scheduling

Variants

LinearRegression

Linear regression for simple predictions

SVM

Support Vector Machine for classification

RandomForest

Random Forest for ensemble learning

GradientBoosting

Gradient Boosting for performance optimization

NeuralNetwork

Neural Network for complex patterns

EnsembleMethod

Ensemble method combining multiple algorithms

DeepRL

Deep Reinforcement Learning

GraphNN

Graph Neural Network for topology-aware scheduling

Trait Implementations

impl Clone for MLAlgorithm

fn clone(&self) -> MLAlgorithm

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for MLAlgorithm

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for MLAlgorithm

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl PartialEq for MLAlgorithm

fn eq(&self, other: &MLAlgorithm) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Serialize for MLAlgorithm

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl Eq for MLAlgorithm

impl StructuralPartialEq for MLAlgorithm