Fixing test results

Author: mmerce

bigml/ensemble.py

@@ -214,7 +214,6 @@ def __init__(self, ensemble, api=None, max_models=None, cache_get=None,
                 # avoid checking fields because of old ensembles
                 ensemble = retrieve_resource(self.api, self.resource_id,
                                              no_check_fields=True)
-
             self.parent_id = ensemble.get('object', {}).get('dataset')
             self.name = ensemble.get('object', {}).get('name')
             self.description = ensemble.get('object', {}).get('description')

bigml/tests/test_14_create_evaluations.py

@@ -194,7 +194,7 @@ def test_scenario4(self):
                    "evaluation_wait", "metric", "value"]
         examples = [
             ['data/iris.csv', '50', '50', '800', '80', 'average_phi',
-             '0.97007']]
+             '0.98029']]
         for example in examples:
             example = dict(zip(headers, example))
             show_method(self, self.bigml["method"], example)

bigml/tests/test_36_compare_predictions.py

@@ -77,7 +77,7 @@ def test_scenario1(self):
              'Iris-versicolor', '{}'],
             ['data/iris_missing2.csv', '30', '50', '60', '{}', '000004',
              'Iris-versicolor', '{}'],
-            ['data/grades.csv', '30', '50', '60', '{}', '000005', 55.6560,
+            ['data/grades.csv', '30', '50', '60', '{}', '000005', 47.04852,
              '{}'],
             ['data/spam.csv', '30', '50', '60', '{}', '000000', 'ham', '{}']]
         show_doc(self.test_scenario1)

bigml/tests/test_40_local_from_file.py

@@ -213,7 +213,7 @@ def test_scenario4(self):
             ['data/iris.csv', '10', '10', '500', './tmp/deepnet.json', {},
              'Iris-versicolor', '{}'],
             ['data/iris.csv', '10', '10', '500', './tmp/deepnet_dft.json', {},
-             'Iris-virginica', '{"default_numeric_value": "maximum"}']]
+             'Iris-versicolor', '{"default_numeric_value": "maximum"}']]
         for example in examples:
             example = dict(zip(headers, example))
             show_method(self, self.bigml["method"], example)

bigml/tests/test_49_local_pipeline.py

@@ -210,28 +210,28 @@ def test_scenario4(self):
         examples = [
             ['data/dates2.csv', '20', '45', '160',
              '{"time-1": "1910-05-08T19:10:23.106", "cat-0":"cat2"}',
-             '000002', -0.02616, "pipeline1"],
+             '000002', -0.4264, "pipeline1"],
             ['data/dates2.csv', '20', '45', '160',
              '{"time-1": "2011-04-01T00:16:45.747", "cat-0":"cat2"}',
-             '000002', 0.13352, "pipeline2"],
+             '000002', 0.11985, "pipeline2"],
             ['data/dates2.csv', '20', '45', '160',
              '{"time-1": "1969-W29-1T17:36:39Z", "cat-0":"cat1"}',
-             '000002', 0.10071, "pipeline3"],
+             '000002', -0.08211, "pipeline3"],
             ['data/dates2.csv', '20', '45', '160',
              '{"time-1": "1920-06-45T20:21:20.320", "cat-0":"cat1"}',
-             '000002', 0.10071, "pipeline4"],
+             '000002', -0.08211, "pipeline4"],
             ['data/dates2.csv', '20', '45', '160',
              '{"time-1": "2001-01-05T23:04:04.693", "cat-0":"cat2"}',
-             '000002', 0.15235, "pipeline5"],
+             '000002', 0.00388, "pipeline5"],
             ['data/dates2.csv', '20', '45', '160',
              '{"time-1": "1950-11-06T05:34:05.602", "cat-0":"cat1"}',
-             '000002', -0.07686, "pipeline6"],
+             '000002', -0.04976, "pipeline6"],
             ['data/dates2.csv', '20', '45', '160',
              '{"time-1": "1932-01-30T19:24:11.440",  "cat-0":"cat2"}',
-             '000002', 0.0017, "pipeline7"],
+             '000002', -0.36264, "pipeline7"],
             ['data/dates2.csv', '20', '45', '160',
              '{"time-1": "Mon Jul 14 17:36 +0000 1969", "cat-0":"cat1"}',
-             '000002', 0.10071, "pipeline8"]]
+             '000002', -0.08211, "pipeline8"]]
         show_doc(self.test_scenario4)
         for example in examples:
             example = dict(zip(headers, example))