Enum AlgorithmFamily 

pub enum AlgorithmFamily {
    Linear,
    TreeBased,
    Ensemble,
    NeighborBased,
    SVM,
    NaiveBayes,
    NeuralNetwork,
    GaussianProcess,
    DiscriminantAnalysis,
    Dummy,
}

Algorithm family categories for classification and regression

Variants

Linear

Linear models (LogisticRegression, LinearRegression, etc.)

TreeBased

Tree-based models (DecisionTree, RandomForest, etc.)

Ensemble

Ensemble methods (AdaBoost, Stacking, etc.)

NeighborBased

Neighbor-based models (KNN, etc.)

SVM

Support Vector Machines

NaiveBayes

Naive Bayes classifiers

NeuralNetwork

Neural networks

GaussianProcess

Gaussian processes

DiscriminantAnalysis

Discriminant analysis

Dummy

Dummy/baseline models

Trait Implementations

impl Clone for AlgorithmFamily

fn clone(&self) -> AlgorithmFamily

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for AlgorithmFamily

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

Formats the value using the given formatter.

impl Display for AlgorithmFamily

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

Formats the value using the given formatter.

impl Hash for AlgorithmFamily

fn hash<__H: Hasher>(&self, state: &mut __H)

Feeds this value into the given Hasher.

fn hash_slice<H>(data: &[Self], state: &mut H)

where H: Hasher, Self: Sized,

Feeds a slice of this type into the given Hasher.

impl PartialEq for AlgorithmFamily

fn eq(&self, other: &AlgorithmFamily) -> 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 Eq for AlgorithmFamily

impl StructuralPartialEq for AlgorithmFamily