Categoría: TUHH – Machine Learning – Python

math.pow

def gen_binary_permutations(n, max_samples=0): perm = [] n_samples = min(len(np.arange(2 * n, 2 * (n + 1))), max_samples) if n_samples > 0: rng = default_rng() if n < 5:p numbers = rng.choice(np.arange(2 *...

random.random()

figure_data = init_2D_linear_separation_plot(C_train, NotC_train, p.w, R)

linalg.norm

zip()

y = np.sign(weighted_sum) if y == 0: y = 1

np.arccos

arrange

default_rgn (rgn.choice)