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I am using Azure and Spark version is '2.1.1.2.6.2.3-1

I have saved my model using the following command: 

def fit_LR(training,testing,adl_root_path,location,modelName):
    training.cache()
    lr = LinearRegression(featuresCol = 'features',labelCol = 'ZZ_TIME',solver="auto",maxIter=100)
    lr_model = lr.fit(training)
    testing.cache()

    lr_outpath = adl_root_path + "Model/Sprint6Results/RUN/" + str(location) + str(modelName)

    lr_model_save = lr.write().overwrite().save(lr_outpath)

When I tried to use the model and reloaded it 

saved_model_path = adl_root_path + "Model/Sprint6Results/RUN/" + str(location) + str(modelName)
reloaded_model = LinearRegression.load(saved_model_path)
testing.cache()
reloaded_model.transform

The error I get is this:

'LinearRegression' object has no attribute 'transform'
Traceback (most recent call last):
AttributeError: 'LinearRegression' object has no attribute 'transform'

All the examples that I have found seemed to tell me that I should have the ability to predict using this new data from the saved model but I seemed to be missing a step..

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1 Answers1

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There was a mistake. I should be saving the fit of the model and not just the LinearRegression Function

lr_model_save = lr_model.write().overwrite().save(lr_outpath)

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