faux release for staging testing
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@@ -74,7 +74,8 @@ class Segmentation(object):
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(target, features, target_mean,
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feature_means) = self.clean_data(query, variable, feature_columns)
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model_storage.create_model_table()
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if model_name:
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model_storage.create_model_table()
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# find model if it exists and is specified
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if model_name is not None:
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@@ -90,7 +91,8 @@ class Segmentation(object):
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rowid = self.data_provider.get_segmentation_data(params)
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# store the model for later use
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model_storage.set_model(model, model_name, feature_columns)
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if model_name:
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model_storage.set_model(model, model_name, feature_columns)
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return zip(rowid[0]['ids'], result, accuracy_array)
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def predict_segment(self, model, feature_columns, target_query,
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