def test_save_and_load(self):
metric = Metric({"name": "logloss"})
rf = RandomForestAlgorithm({"ml_task": "binary_classification"})
rf.fit(self.X, self.y)
y_predicted = rf.predict(self.X)
loss = metric(self.y, y_predicted)
with tempfile.NamedTemporaryFile() as tmp:
rf.save(tmp.name)
rf2 = RandomForestAlgorithm({"ml_task": "binary_classification"})
rf2.load(tmp.name)
y_predicted = rf2.predict(self.X)
loss2 = metric(self.y, y_predicted)
assert_almost_equal(loss, loss2)
def test_save_and_load(self):
metric = Metric({"name": "logloss"})
rf = RandomForestAlgorithm({"ml_task": "binary_classification"})
rf.fit(self.X, self.y)
y_predicted = rf.predict(self.X)
loss = metric(self.y, y_predicted)
filename = os.path.join(tempfile.gettempdir(), os.urandom(12).hex())
rf.save(filename)
rf2 = RandomForestAlgorithm({"ml_task": "binary_classification"})
rf2.load(filename)
#Finished with the file, delete it
os.remove(filename)
y_predicted = rf2.predict(self.X)
loss2 = metric(self.y, y_predicted)
assert_almost_equal(loss, loss2)