from sklearn.neural_network import MLPClassifier
import numpy as np
X = [[0, 0], [0, 1], [1, 0], [1, 1]]
y = [1, 0, 0, 1]
net = MLPClassifier(solver='lbfgs', hidden_layer_sizes=(2,), random_state=6)
net.fit(X, y)
net.predict([0, 0])

241e2e743783618940793d2d67d4a0ca5dda7d94
<mask token>

<mask token>
net.fit(X, y)
net.predict([0, 0])

<mask token>
X = [[0, 0], [0, 1], [1, 0], [1, 1]]
y = [1, 0, 0, 1]
net = MLPClassifier(solver='lbfgs', hidden_layer_sizes=(2,), random_state=6)
net.fit(X, y)
net.predict([0, 0])

from sklearn.neural_network import MLPClassifier
import numpy as np
X = [[0, 0], [0, 1], [1, 0], [1, 1]]
y = [1, 0, 0, 1]
net = MLPClassifier(solver='lbfgs', hidden_layer_sizes=(2,), random_state=6)
net.fit(X, y)
net.predict([0, 0])
