Struct vikos::model::Linear

pub struct Linear<V: Vector> {
    pub m: V,
    pub c: V::Scalar,
}

Models the target as y = m * x + c

Fields

m: V

Slope

c: V::Scalar

Offset

Trait Implementations

impl<V: Debug + Vector> Debug for Linear<V> where V::Scalar: Debug

fn fmt(&self, __arg_0: &mut Formatter) -> Result

Formats the value using the given formatter.

impl<V: Clone + Vector> Clone for Linear<V> where V::Scalar: Clone

fn clone(&self) -> Linear<V>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<V: Default + Vector> Default for Linear<V> where V::Scalar: Default

fn default() -> Linear<V>

Returns the "default value" for a type.

impl<V: Decodable + Vector> Decodable for Linear<V> where V::Scalar: Decodable

fn decode<__DV: Decoder>(__arg_0: &mut __DV) -> Result<Linear<V>, __DV::Error>

impl<V: Encodable + Vector> Encodable for Linear<V> where V::Scalar: Encodable

fn encode<__SV: Encoder>(&self, __arg_0: &mut __SV) -> Result<(), __SV::Error>

impl<V> Model for Linear<V> where V: Vector<Scalar=f64>

type Input = V

Input features

fn predict(&self, input: &V) -> V::Scalar

Predicts a target for the inputs based on the internal coefficents

fn num_coefficents(&self) -> usize

The number of internal coefficents this model depends on

fn gradient(&self, coefficent: usize, input: &V) -> V::Scalar

Value predict derived by the n-th coefficent at input

fn coefficent(&mut self, coefficent: usize) -> &mut V::Scalar

Mutable reference to the n-th coefficent