Struct PassiveAggressive 

pub struct PassiveAggressive { /* private fields */ }

Passive-Aggressive classifier (Crammer et al. 2006).

Labels must be in {−1, +1}. The PA family uses the hinge loss ℓ = max(0, 1 − y(w·x + b)) and then computes a closed-form minimal weight update.

Implementations

impl PassiveAggressive

pub fn new(n_features: usize, variant: PAVariant) -> Self

Create a new PA classifier. variant controls the update rule.

pub fn with_aggressiveness(self, c: f64) -> Result<Self, OnlineError>

Set the aggressiveness parameter C (must be positive).

pub fn stats(&self) -> &OnlineStats

Reference to running statistics.

Trait Implementations

impl Clone for PassiveAggressive

fn clone(&self) -> PassiveAggressive

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for PassiveAggressive

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

Formats the value using the given formatter.

impl OnlineLearner for PassiveAggressive

fn update( &mut self, features: &[f64], label: f64, ) -> Result<OnlineUpdateResult, OnlineError>

Update model on a single (features, label) pair. Returns update stats.

fn predict(&self, features: &[f64]) -> Result<f64, OnlineError>

Predict class label or regression value for features.

fn n_updates(&self) -> usize

Number of updates seen so far.

fn weights(&self) -> &[f64]

Current weight vector (without bias).