GradientDescentReg

class mlpractice.gradient_descent.GradientDescentReg(W0: numpy.ndarray, lambda_: float, mu: float = 0.01, S0: float = 1, P: float = 0.5)

Full gradient descent with regularization class.

Parameters
mufloat

l2 regularization coefficient.

Attributes
mufloat

l2 regularization coefficient.

Methods

calc_gradient(X, Y)

Calculating MSE gradient.

step(X, Y, iteration)

Descending step.

update_weights(gradient, iteration)

Changing weights with respect to gradient.

calc_gradient(X: numpy.ndarray, Y: numpy.ndarray) numpy.ndarray

Calculating MSE gradient.

Parameters
Xnp.ndarray

Features.

Ynp.ndarray

Targets.

Returns
gradientnp.ndarray

Calculating gradient.

update_weights(gradient: numpy.ndarray, iteration: int) numpy.ndarray

Changing weights with respect to gradient.

Parameters
gradientnp.ndarray

Gradient of MSE.

iterationint

Iteration number.

Returns
weigh_diffnp.ndarray

Weight difference.