Enum MetaLearningStrategy 

pub enum MetaLearningStrategy {
    LinearRegression,
    Ridge(Float),
    Lasso(Float),
    ElasticNet(Float, Float),
    LogisticRegression,
    SVM,
    NeuralNetwork,
    BayesianAveraging,
}

Meta-learning strategies for combining predictions

Variants

LinearRegression

Simple linear regression (default)

Ridge(Float)

Ridge regression with L2 regularization

Lasso(Float)

Lasso regression with L1 regularization

ElasticNet(Float, Float)

Elastic net with combined L1/L2 regularization

LogisticRegression

Logistic regression for classification

SVM

Support Vector Machine

NeuralNetwork

Neural network meta-learner

BayesianAveraging

Bayesian averaging

Trait Implementations

impl Clone for MetaLearningStrategy

fn clone(&self) -> MetaLearningStrategy

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for MetaLearningStrategy

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

Formats the value using the given formatter.

impl PartialEq for MetaLearningStrategy

fn eq(&self, other: &MetaLearningStrategy) -> 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 Copy for MetaLearningStrategy

impl StructuralPartialEq for MetaLearningStrategy