Struct NeuralNetwork

pub struct NeuralNetwork { /* private fields */ }

A simple feedforward neural network with one hidden layer.

Implementations

impl NeuralNetwork

pub fn new( input_size: usize, hidden_size: usize, output_size: usize, rng: Option<&mut StdRng>, ) -> Self

Creates a new neural network with the given sizes for input, hidden, and output layers. The weights and biases are initialized randomly.

pub fn learning_rate(&self) -> f64

Returns the learning rate of the neural network.

pub fn set_learning_rate(&mut self, learning_rate: f64)

Sets the learning rate for the neural network.

pub fn activation_function(&self) -> &ActivationFunction

Returns the activation function of the neural network.

pub fn set_activation_function( &mut self, activation_function: ActivationFunction, )

Sets the activation function for the neural network.

pub fn predict(&self, input: Vec<f64>) -> Vec<f64>

Predicts the output for the given input using the neural network.

pub fn train(&mut self, input: Vec<f64>, target: Vec<f64>)

Trains the neural network using the given input and target output. The input and target should be vectors of the same length as the input and output sizes of the network. The training process involves forward propagation and backpropagation to adjust the weights and biases.

pub fn mutate(&mut self, rng: &mut StdRng, mutation_rate: f64)

Trait Implementations

impl Clone for NeuralNetwork

fn clone(&self) -> NeuralNetwork

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for NeuralNetwork

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

Formats the value using the given formatter.

impl Default for NeuralNetwork

fn default() -> NeuralNetwork

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for NeuralNetwork

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

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Serialize for NeuralNetwork

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

where __S: Serializer,

Serialize this value into the given Serde serializer.