def test_classification(self):
unicorn = UnicornML({"file": "./data/abalone.csv"})
X = np.concatenate((unicorn.X_train, unicorn.X_test), axis=0)
y = np.concatenate((unicorn.y_train, unicorn.y_test), axis=0)
unicorn.Rainbow()
yatt = unicorn.predict(X)
accuracy = unicorn.evaluate(y, yatt)
print("Accuracy %f" % accuracy)
self.assertEqual("foo".upper(), "FOO")
def test_linearRegression(self):
unicorn = UnicornML({"file": "./data/housing.csv"})
X = np.concatenate((unicorn.X_train, unicorn.X_test), axis=0)
y = np.concatenate((unicorn.y_train, unicorn.y_test), axis=0)
unicorn.Rainbow()
yatt = unicorn.predict(X)
mse = unicorn.evaluate(y, yatt)
print("mse: %f" % mse)
self.assertEqual("foo".upper(), "FOO")
def test_linearRegression(self):
unicorn = UnicornML(
{"images": "/home/joseb/Desktop/aa2/aula6/cats_and_dogs_small"}, {
"height": 150,
"width": 150,
"depth": 3,
"fine_tuning": False
})
unicorn.Rainbow()
acc = unicorn.evaluate(1, 1)
print("acc: %f" % acc)
self.assertEqual("foo".upper(), "FOO")