def test_multiclass_probas():
mlp = MLP(epochs=500,
eta=0.5,
hidden_layers=[10],
optimizer='gradientdescent',
activations=['logistic'],
minibatches=1,
random_seed=1)
mlp.fit(X, y)
idx = [0, 50, 149] # sample labels: 0, 1, 2
y_pred = mlp.predict_proba(X[idx])
exp = np.array([[1.0, 0.0, 0.0], [0.0, 0.9, 0.1], [0.0, 0.1, 0.9]])
np.testing.assert_almost_equal(y_pred, exp, 1)
def test_multiclass_probas():
mlp = MLP(epochs=500,
eta=0.5,
hidden_layers=[10],
optimizer='gradientdescent',
activations=['logistic'],
minibatches=1,
random_seed=1)
mlp.fit(X, y)
idx = [0, 50, 149] # sample labels: 0, 1, 2
y_pred = mlp.predict_proba(X[idx])
exp = np.array([[1.0, 0.0, 0.0],
[0.0, 0.9, 0.1],
[0.0, 0.1, 0.9]])
np.testing.assert_almost_equal(y_pred, exp, 1)
