def setUp(self):
self.le = LogisticEnsemble(models=[IdModel()])
inp = [{
"user": 10,
"item": 100
}, {
"user": 10,
"item": 110
}, {
"user": 12,
"item": 120
}]
self.df = pd.DataFrame(inp)
class LogisticTest(unittest.TestCase):
def setUp(self):
self.le = LogisticEnsemble(models=[IdModel()])
inp = [{
"user": 10,
"item": 100
}, {
"user": 10,
"item": 110
}, {
"user": 12,
"item": 120
}]
self.df = pd.DataFrame(inp)
def test_construct_features(self):
self.le._prepare_feature_extraction(self.df)
self.assertEqual(self.le._user_count, {10: 2, 12: 1})
def test_extract_features(self):
self.le._prepare_feature_extraction(self.df)
features = self.le._extract_features(10, 5)
self.assertEqual(features, ([2, 5], 1))
def test_prepare_data(self):
X, Y = self.le.prepare_data(self.df)
self.assertEqual(len(X), 6)
self.assertEqual(len(Y), 6)
def test_fit(self):
self.le.fit(self.df)
self.assertIsNotNone(self.le.model)
def test_predict(self):
self.le.fit(self.df)
self.assertIsInstance(self.le.get_score(10, 110), float)
class LogisticTest(unittest.TestCase):
def setUp(self):
self.le = LogisticEnsemble(models=[IdModel()])
inp = [{"user": 10, "item": 100}, {"user": 10,"item": 110},
{"user": 12, "item": 120}]
self.df = pd.DataFrame(inp)
def test_construct_features(self):
self.le._prepare_feature_extraction(self.df)
self.assertEqual(self.le._user_count, {10: 2, 12: 1})
def test_extract_features(self):
self.le._prepare_feature_extraction(self.df)
features = self.le._extract_features(10, 5)
self.assertEqual(features, ([2, 5], 1))
def test_prepare_data(self):
X, Y = self.le.prepare_data(self.df)
self.assertEqual(len(X), 6)
self.assertEqual(len(Y), 6)
def test_fit(self):
self.le.fit(self.df)
self.assertIsNotNone(self.le.model)
def test_predict(self):
self.le.fit(self.df)
self.assertIsInstance(self.le.get_score(10, 110), float)
def setUp(self):
self.le = LogisticEnsemble(models=[IdModel()])
inp = [{"user": 10, "item": 100}, {"user": 10,"item": 110},
{"user": 12, "item": 120}]
self.df = pd.DataFrame(inp)
def setUp(self):
self.le = LogisticEnsemble(models=[IdModel()])
inp = [{'user': 10, 'item': 100}, {'user': 10,'item': 110},
{'user': 12,'item': 120}]
self.df = pd.DataFrame(inp)
