Struct VariationalLogisticRegression

pub struct VariationalLogisticRegression {
    pub bound: f64,
    /* private fields */
}

Represents a logistic regression model trained via variational inference

Fields

bound: f64

Variational lower bound

Implementations

impl VariationalLogisticRegression

pub fn train( features: impl Features, labels: impl BinaryLabels, config: &LogisticTrainConfig, ) -> Result<VariationalLogisticRegression, RegressionError>

Trains the model on the provided data

Arguments

features - The feature values (in row-major orientation) labels - The vector of corresponding labels config - The training configuration

Trait Implementations

impl Clone for VariationalLogisticRegression

fn clone(&self) -> VariationalLogisticRegression

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<'de> Deserialize<'de> for VariationalLogisticRegression

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Serialize for VariationalLogisticRegression

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl VariationalRegression<BernoulliDistribution> for VariationalLogisticRegression

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

Computes the predictive distribution for the provided features

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

Provides the estimated model weights

fn bias(&self) -> Option<f64>

Provides the estimated model bias, if specified for training