def test_rdf(self):
from sklearn.datasets import load_iris
iris = load_iris()
data = iris.data
target = convert_target(iris.target)
normalise_data = normalise(data)
rdf = RDFNetwork(normalise_data, target, 1)
rdf.train()
print rdf.score(normalise_data, target)
def a_test_iris(self):
from sklearn.datasets import load_iris
iris = load_iris()
data = iris.data
normalised_data = normalise(data)
target = convert_target(iris.target)
print '======================'
mlp = MLP(normalised_data, target, hidden_node=17,
itercount=2005, theta=0.9, mode='softmax')
mlp.train()
self.assertEquals(100, mlp.score(normalised_data, target))
self.assertEquals([[0, 0, 1]], mlp.predict(np.array([[5,5,5,2]])))
