def test_fit(self):
X = numpy.array([[2.0, 3.0]])
y = numpy.array(1.0 / (1.0 + numpy.exp(-1.0/(1.0+numpy.exp(-numpy.dot(X,X.transpose()))))))
thresh = .0000001
net = BackpropNetwork([2,4,1],thresh=thresh)
net.fit(X,y)
error = 0.5*((net.predict(X)[0,0] - y[0,0])**2)
assert_true(error < thresh)
def test_predict(self):
X = numpy.array([[2.0]])
y = numpy.array(1.0 / (1.0 + numpy.exp(-1.0/(1.0+numpy.exp(-X)))))
net = BackpropNetwork([1,1,1])
assert_almost_equal(net.predict(X)[0,0],y[0,0])
