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.