Struct LinearChainCRF 

pub struct LinearChainCRF {
    pub n_labels: usize,
    pub n_features: usize,
    pub max_iter: usize,
    pub learning_rate: f32,
    pub l2_penalty: f32,
    pub tol: f32,
    /* private fields */
}

Linear-chain Conditional Random Field

Used for sequence labeling tasks like:

• Named Entity Recognition (NER)
• Part-of-Speech (POS) tagging
• Chunking
• Segmentation

Fields

n_labels: usize

n_features: usize

max_iter: usize

learning_rate: f32

l2_penalty: f32

tol: f32

Implementations

impl LinearChainCRF

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

pub fn max_iter(self, iter: usize) -> Self

pub fn learning_rate(self, lr: f32) -> Self

pub fn l2_penalty(self, penalty: f32) -> Self

pub fn fit(&mut self, sequences: &[Tensor], labels: &[Tensor])

Fit the CRF using stochastic gradient descent

pub fn predict(&self, sequence: &Tensor) -> Tensor

Predict label sequence using Viterbi algorithm

pub fn predict_marginals(&self, sequence: &Tensor) -> Tensor

Predict marginal probabilities for each position