Enum Solver 

#[non_exhaustive]
pub enum Solver {
    Lbfgs,
    GradientDescent,
}

Solver algorithm for logistic regression.

L-BFGS is the default and recommended solver — it converges in ~10-20 iterations vs 200+ for gradient descent, matching scikit-learn’s default.

Variants (Non-exhaustive)

Non-exhaustive enums could have additional variants added in future. Therefore, when matching against variants of non-exhaustive enums, an extra wildcard arm must be added to account for any future variants.

Lbfgs

L-BFGS quasi-Newton optimizer (default). Fast, recommended.

GradientDescent

Vanilla batch gradient descent. Slower, kept for backward compatibility.

Trait Implementations

impl Clone for Solver

fn clone(&self) -> Solver

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for Solver

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

Formats the value using the given formatter.

impl Default for Solver

fn default() -> Solver

Returns the “default value” for a type.

impl PartialEq for Solver

fn eq(&self, other: &Solver) -> 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 Solver

impl Eq for Solver

impl StructuralPartialEq for Solver