Struct ConvolutionalKernelFeatures 

pub struct ConvolutionalKernelFeatures {
    pub n_components: usize,
    pub kernel_size: usize,
    pub stride: usize,
    pub padding: usize,
    pub activation: ActivationFunction,
}

Convolutional kernel features using random convolutions ConvolutionalKernelFeatures

Fields

n_components: usize

n_components

kernel_size: usize

kernel_size

stride: usize

stride

padding: usize

padding

activation: ActivationFunction

activation

Implementations

impl ConvolutionalKernelFeatures

pub fn new(n_components: usize, kernel_size: usize) -> Self

pub fn stride(self, stride: usize) -> Self

pub fn padding(self, padding: usize) -> Self

pub fn activation(self, activation: ActivationFunction) -> Self

Trait Implementations

impl Clone for ConvolutionalKernelFeatures

fn clone(&self) -> ConvolutionalKernelFeatures

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for ConvolutionalKernelFeatures

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

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for ConvolutionalKernelFeatures

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

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Fit<ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>, ()> for ConvolutionalKernelFeatures

type Fitted = FittedConvolutionalKernelFeatures

The fitted model type

fn fit(self, _x: &Array2<f64>, _y: &()) -> Result<Self::Fitted>

Fit the model to the provided data with validation

fn fit_with_validation( self, x: &X, y: &Y, _x_val: Option<&X>, _y_val: Option<&Y>, ) -> Result<(Self::Fitted, FitMetrics), SklearsError>

where Self: Sized,

Fit with custom validation and early stopping

impl Serialize for ConvolutionalKernelFeatures

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

where __S: Serializer,

Serialize this value into the given Serde serializer.