Enum MLAlgorithm 

pub enum MLAlgorithm {
    DeepNeuralNetwork,
    RandomForest,
    GradientBoosting,
    SupportVectorMachine,
    GaussianProcess,
    EnsembleMethods,
    ReinforcementLearning,
    QuantumNeuralNetwork,
    GraphNeuralNetwork,
    TransformerNetwork,
    BayesianNetwork,
    Custom(String),
}

ML algorithms available

Variants

DeepNeuralNetwork

Deep Neural Network

RandomForest

Random Forest

GradientBoosting

Gradient Boosting

SupportVectorMachine

Support Vector Machine

GaussianProcess

Gaussian Process

EnsembleMethods

Ensemble Methods

ReinforcementLearning

Reinforcement Learning

QuantumNeuralNetwork

Quantum Neural Network

GraphNeuralNetwork

Graph Neural Network

TransformerNetwork

Transformer Networks

BayesianNetwork

Bayesian Networks

Custom(String)

Custom algorithm

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 StructuralPartialEq for MLAlgorithm