pub struct GradientDesc { /* private fields */ }
Expand description

Batch Gradient Descent algorithm

Implementations

Construct a gradient descent algorithm.

Requires the step size and iteration count to be specified.

Examples
use rusty_machine::learning::optim::grad_desc::GradientDesc;

let gd = GradientDesc::new(0.3, 10000);

Trait Implementations

Returns a copy of the value. Read more
Performs copy-assignment from source. Read more
Formats the value using the given formatter. Read more

The default gradient descent algorithm.

The defaults are:

  • alpha = 0.3
  • iters = 100
Returns the “default value” for a type. Read more
Return the optimized parameter using gradient optimization. Read more

Auto Trait Implementations

Blanket Implementations

Gets the TypeId of self. Read more
Immutably borrows from an owned value. Read more
Mutably borrows from an owned value. Read more

Returns the argument unchanged.

Calls U::from(self).

That is, this conversion is whatever the implementation of [From]<T> for U chooses to do.

The resulting type after obtaining ownership.
Creates owned data from borrowed data, usually by cloning. Read more
Uses borrowed data to replace owned data, usually by cloning. Read more
The type returned in the event of a conversion error.
Performs the conversion.
The type returned in the event of a conversion error.
Performs the conversion.