Struct opensrdk_kernel_method::neural_network::deep_neural_network::DeepNeuralNetwork

pub struct DeepNeuralNetwork<'a> { /* private fields */ }

https://arxiv.org/abs/1711.00165

Implementations

impl<'a> DeepNeuralNetwork<'a>

pub fn new(layers: Vec<&'a dyn ActivationFunction>) -> Self

Trait Implementations

impl<'a, R> Add<R> for DeepNeuralNetwork<'a>where
    R: PositiveDefiniteKernel<Vec<f64>>,

type Output = KernelAdd<DeepNeuralNetwork<'a>, R, Vec<f64, Global>>

The resulting type after applying the + operator.

fn add(self, rhs: R) -> Self::Output

Performs the + operation.

impl<'a> Clone for DeepNeuralNetwork<'a>

fn clone(&self) -> DeepNeuralNetwork<'a>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<'a> Debug for DeepNeuralNetwork<'a>

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

Formats the value using the given formatter.

impl<'a, R> Mul<R> for DeepNeuralNetwork<'a>where
    R: PositiveDefiniteKernel<Vec<f64>>,

type Output = KernelMul<DeepNeuralNetwork<'a>, R, Vec<f64, Global>>

The resulting type after applying the * operator.

fn mul(self, rhs: R) -> Self::Output

Performs the * operation.

impl<'a> ParamsDifferentiableKernel<Vec<f64, Global>> for DeepNeuralNetwork<'a>

fn ln_diff_params(
    &self,
    params: &[f64],
    x: &Vec<f64>,
    xprime: &Vec<f64>
) -> Result<Vec<f64>, KernelError>

impl<'a> PositiveDefiniteKernel<Vec<f64, Global>> for DeepNeuralNetwork<'a>

fn params_len(&self) -> usize

fn value(
    &self,
    params: &[f64],
    x: &Vec<f64>,
    xprime: &Vec<f64>
) -> Result<f64, KernelError>

impl<'a> ValueDifferentiableKernel<Vec<f64, Global>> for DeepNeuralNetwork<'a>

fn ln_diff_value(
    &self,
    params: &[f64],
    x: &Vec<f64>,
    xprime: &Vec<f64>
) -> Result<Vec<f64>, KernelError>