update tests
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@ -1,5 +1,5 @@
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\pset format unaligned
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\pset format unaligned
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\set ECHO all
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\set ECHO none
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\i test/fixtures/ml_values.sql
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\i test/fixtures/ml_values.sql
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SELECT cdb_crankshaft._cdb_random_seeds(1234);
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SELECT cdb_crankshaft._cdb_random_seeds(1234);
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SELECT prediction from cdb_crankshaft.CDB_CreateAndPredictSegment('select target,x1,x2,x3 from ml_values where class= $$train$$','target','select cartodb_id, target,x1,x2,x3 from ml_values where class=$$test$$') limit 20
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SELECT prediction FROM cdb_crankshaft.CDB_CreateAndPredictSegment('SELECT target, x1, x2, x3 FROM ml_values WHERE class = $$train$$','target','SELECT cartodb_id, target, x1, x2, x3 FROM ml_values WHERE class = $$test$$') LIMIT 20;
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@ -23,6 +23,11 @@ class SegmentationTest(unittest.TestCase):
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else:
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else:
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return [dict( zip(['x1','x2','x3','target', 'cartodb_id'],[x1,x2,x3,y,cartodb_id]))]
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return [dict( zip(['x1','x2','x3','target', 'cartodb_id'],[x1,x2,x3,y,cartodb_id]))]
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def test_replace_nan_with_mean(self):
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test_array = np.array([1.2, np.nan, 3.2, np.nan, np.nan])
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def test_create_and_predict_segment(self):
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def test_create_and_predict_segment(self):
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n_samples = 1000
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n_samples = 1000
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