def test(file_path):
# Cargando data
data_test = "./csv_files/KDDTest.txt"
xv, yv = load_data(data_test)
Xv = np.vstack([xv, np.full((1, xv.shape[1]), 1)])
w1, w2 = load_w()
D = Xv.shape[0]
wh = np.reshape(w1, (Nh, D))
H = activation(wh, Xv)
zv = np.matmul(w2, H)
accuracy, fscore = metrica(zv, yv)
save(accuracy, fscore)
def fitness(Xe, ye, Nh, X, Cpinv):
N, D = Xe.shape
Np = configs.Np
# Shape (Np)
W2 = np.zeros((Np, Nh)) # TODO: inicializar los pesos
# Posiblemente dejemos la cagá
MSE = np.full(Np, -1.0)
for i in range(Np):
p = X[i, :]
w1 = np.reshape(p, (D, Nh))
H = activation(Xe, w1)
W2[i, :] = mlp_pinv(H, ye, configs.C)
ze = W2[i, :].dot(np.transpose(H))
MSE[i] = np.sqrt(mse(ye, ze)) # Error cuadratico medio
# FIXME: esto está mal porque da cero siempre
return MSE, W2
import numpy as np
from activation import activation
act = activation()
def init_network():
network = {}
network['w1'] = np.array([[0.1, 0.3, 0.5], [0.2, 0.4, 0.6]])
network['b1'] = np.array([0.1, 0.2, 0.3])
network['w2'] = np.array([[0.1, 0.4], [0.2, 0.5], [0.3, 0.6]])
network['b2'] = np.array([0.1, 0.2])
return network
def forward(network, x):
w1, w2 = network['w1'], network['w2']
b1, b2 = network['b1'], network['b2']
a1 = np.dot(x, w1) + b1
z1 = act.sigmoid(a1)
a2 = np.dot(z1, w2) + b2
return a2
# --------- メイン処理 -----------
network = init_network()
x = np.array([1.0, 0.5])
y = forward(network, x)