pub trait Optimizable {
    type Inputs;
    type Targets;

    fn compute_grad(
        &self,
        params: &[f64],
        inputs: &Self::Inputs,
        targets: &Self::Targets
    ) -> (f64, Vec<f64>); }
Expand description

Trait for models which can be gradient-optimized.

Required Associated Types

The input data type to the model.

The target data type to the model.

Required Methods

Compute the gradient for the model.

Implementors

Computing the gradient of the underlying Logistic Regression model.

The gradient is given by

XT(h(Xb) - y) / m

where h is the sigmoid function and b the underlying model parameters.

Compute the gradient of the Neural Network using the back propagation algorithm.