Struct BackProp

pub struct BackProp {
    pub parameters: LearningParameters,
    pub hidden_derivative: fn(f64) -> f64,
    pub output_derivative: fn(f64) -> f64,
    /* private fields */
}

Fields

parameters: LearningParameters

hidden_derivative: fn(f64) -> f64

output_derivative: fn(f64) -> f64

Implementations

impl BackProp

pub fn new( input_count: usize, hidden_counts: &[usize], output_count: usize, learning_rate: f64, momentum: f64, weight_decay: f64, hidden_activation: fn(f64) -> f64, hidden_derivative: fn(f64) -> f64, output_activation: fn(f64) -> f64, output_derivative: fn(f64) -> f64, ) -> Self

pub fn pulse(&mut self, input: &[f64]) -> Vec<f64>

pub fn back_prop(&mut self, target: &[f64])

pub fn test(&mut self, input: &[f64], target: &[f64]) -> f64

pub fn train( &mut self, min_error: f64, max_epochs: Option<u64>, max_duration: Option<Duration>, train_inputs: &[&[f64]], train_targets: &[&[f64]], test_inputs: &[&[f64]], test_targets: &[&[f64]], ) -> TrainingResult

pub fn save<T: CopyIO>(&self, f: &mut T) -> Result<()>

pub fn load<T: CopyIO>( f: &mut T, hidden_activation: fn(f64) -> f64, hidden_derivative: fn(f64) -> f64, output_activation: fn(f64) -> f64, output_derivative: fn(f64) -> f64, ) -> Result<Self>

Trait Implementations

impl Debug for BackProp

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

Formats the value using the given formatter.

impl PartialEq for BackProp

fn eq(&self, other: &BackProp) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for BackProp