Struct lfa::eval::VectorFunction

pub struct VectorFunction {
    pub weights: Matrix<f64>,
}

Weight-Projection evaluator with vector Vector<f64> output.

Fields

weights: Matrix<f64>

Methods

impl VectorFunction

pub fn new(weights: Matrix<f64>) -> Self

pub fn zeros(n_features: usize, n_outputs: usize) -> Self

Trait Implementations

impl Approximator<Projection> for VectorFunction

type Value = Vector<f64>

fn n_outputs(&self) -> usize

Return the dimensionality of the output value Approximator::Value.

fn evaluate(&self, p: &Projection) -> EvaluationResult<Vector<f64>>

Evaluate the function and return its value.

fn update(&mut self, p: &Projection, errors: Vector<f64>) -> UpdateResult<()>

Update the approximator's estimate for the given input.

fn adapt(
    &mut self,
    new_features: &HashMap<IndexT, IndexSet>
) -> AdaptResult<usize>

Adapt the approximator in light of newly discovered features.

impl Parameterised for VectorFunction

fn weights(&self) -> Matrix<f64>

Return a copy of the approximator weights.

fn n_weights(&self) -> usize

Returns the total number of weights.

impl Clone for VectorFunction

fn clone(&self) -> VectorFunction

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<'de> Deserialize<'de> for VectorFunction

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
    __D: Deserializer<'de>, 

Deserialize this value from the given Serde deserializer.

impl Serialize for VectorFunction

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

Serialize this value into the given Serde serializer.