from sklearn.linear_model import SGDRegressor sgdreg = SGDRegressor(maxiter=1000, tol=1e-3, penalty=None, eta0=0.1) sgd_reg.fit(X, y.ravel()) sgdreg.intercept, sgdreg.coef ...

Variación del hyperparámetro learning rate para optimizar la búsqueda del mínimo global de la función de coste. Primero definimos una función de variación, por ejemplo: def learning_schedule(t): return t0 / (t + t1) Posteriormente llamamos a esa función en cada una de las iteraciones antes de actualizar los parámetros de la red neuronal: eta = learning_schedule(epoch * m + i) ...

A manifold is a connected region. Mathematically, it is a set of points, associated with a neighborhood around each point. From any given point, the manifold locally appears to be a Euclidean space. In everyday life, we experience the surface of the world as a 2-D plane, but it is in fact a spherical manifold in 3-D space. The definition of a neighborhood surrounding each point implies the existence of transformations that can be applied to move on the manifold from one position to a neighbor...