def test_fitSVR(data): model = MetaModel().readCSV(data) model.setResponse("Electricity:Facility [J](Hourly)") model.addPredictor("Environment:Site Outdoor Air Drybulb Temperature [C](Hourly)") model.addPredictor("Environment:Site Outdoor Air Humidity Ratio [kgWater/kgDryAir](Hourly)") model.fitSVR(cost=10, epsilon=0.2).getScores() print(model.scores)
def test_persist(data): model = MetaModel().readCSV(data) model.setResponse("Electricity:Facility [J](Hourly)") model.addPredictor("Environment:Site Outdoor Air Drybulb Temperature [C](Hourly)") model.addPredictor("Environment:Site Outdoor Air Humidity Ratio [kgWater/kgDryAir](Hourly)") model.fitSVR(cost=10, epsilon=0.2).getScores() model.persistMeta('testPickle.p') newModel = pickle.load(open('testPickle.p', 'rb')) print(newModel.scores)