0
$\begingroup$

I'm having troubles generating univariate time series forecasts with Azure Automated Machine Learning (I know...).

What I'm doing

So I have about 5 years worth of monthly observations in a dataframe that looks like this:

date target_value
2015-02-01 123
2015-03-01 456
2015-04-01 789
... ...

I want to forecast target_value based on past values of target_value, i.e. univariate forecasting like ARIMA for instance.
So I am setting up the AutoML forecast like this:

# that's the dataframe as shown above
train_data = Dataset.Tabular.from_delimited_files(path=datastore.path(my_remote_filename))

# ...other code...

forecasting_parameters = ForecastingParameters(
    time_column_name='date',
    forecast_horizon=2,
    target_lags='auto',
    freq='MS'
)

automl_config = AutoMLConfig(task='forecasting',
                             debug_log='automl_forecasting_function.log',
                             primary_metric='normalized_root_mean_squared_error',
                             enable_dnn=True,
                             experiment_timeout_hours=8.0,
                             enable_early_stopping=True,
                             training_data=train_data,
                             compute_target='my-cluster',
                             n_cross_validations=3,
                             verbosity=logging.INFO,
                             max_concurrent_iterations=4,
                             max_cores_per_iteration=-1,
                             label_column_name='target_value',
                             forecasting_parameters=forecasting_parameters)

What the problem is

But AutoML does not seem to generate the forecast for target_value based on past values of target_value. It seems to use the date column as the independent variable! The feature importance chart also shows date as the input feature:

Feature Importance

As a side note: running multivariate forecasts works fine.
When I use a dataset like this, feature_1 and feature_2 are used (i.e. as the X) to forecast target_value (i.e. the y)

date feature_1 feature_2 target_value
2015-02-01 10 7 123
2015-03-01 30 2 456
2015-04-01 20 5 789
... ... ... ...

My questions therefore
How do I need to set up a univariate AutoML forecast to forecast target_value based on past observations target_value?
I assumed generating lagged values for target_value etc. is exactly what AutoML is supposed to do.

Thanks!

$\endgroup$
0
$\begingroup$

I have encountered the same problem as you on Azure ML... that's why I have decided to use the SmartPredict platform.

The difference is that we are more flexible in terms of modules and custom modules, our modules have more parameters, and we take a use case approach. In addition, we also have Autoflow, which allows us to automatically generate a flowchart. And in terms of IT resources, we can also choose the size and type of resources.

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.