.. _sec_forecastingfaq:

FAQ - Time Series
=================


Where can I find more information about the models/metrics?
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Metrics are implemented in the ``autogluon.timeseries.evaluator``
module. We also follow some of the same conventions followed by GluonTS
in their evaluation. Please refer to the GluonTS
`documentation <https://ts.gluon.ai/stable/api/gluonts/gluonts.html>`__
and `github <https://github.com/awslabs/gluon-ts>`__ for further
information.

A detailed description of evaluation metrics is also available at
`here <https://docs.aws.amazon.com/forecast/latest/dg/metrics.html>`__.

How can I get the most accurate forecast predictions?
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Generally setting the ``predictor.fit()`` argument
``presets="best_quality"`` or ``presets="high_quality"`` will result in
high accuracy. Alternative options include manually specifying
hyperparameter search spaces for certain models and manually increasing
the number of hyperparameter optimization trials.

Can I use GPUs for model training?
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Yes! Most of the deep learning models used by ``autogluon.timeseries``
support GPU training. PyTorch models will have GPU enabled by default.
If you also want to use MXNet models, make sure you have installed CUDA
and the GPU version of MXNet. Multi-GPU training is not yet supported.

What machine is best for running ``autogluon.timeseries``?
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

``autogluon.forecasting`` can be run on any machine including your
laptop. Currently it is not necessary to use a GPU to train forecasting
models so CPU machines are fine albeit slower for certain models. We
recommend running on a machine with as much memory as possible (for
instance if using AWS EC2, we recommend `P3
instances <https://aws.amazon.com/ec2/instance-types/p3/>`__) for GPU
support or `M6
instances <https://aws.amazon.com/ec2/instance-types/m6i/>`__ for CPU
training.

Issues not addressed here
~~~~~~~~~~~~~~~~~~~~~~~~~

First search if your issue is addressed in the
`tutorials <index.html>`__,
`documentation <../../api/autogluon.predictor.html>`__, or `Github
issues <https://github.com/autogluon/autogluon/issues>`__ (search both
Closed and Open issues). If it is not there, please open a `new Github
Issue <https://github.com/autogluon/autogluon/issues/new>`__ and clearly
state your issue and clarify how it relates to the module.

If you have a bug, please include: your code (ideally set
``verbosity=4`` which will print out more details), the output printed
during the code execution, and information about your operating system,
Python version, and installed packages (output of ``pip freeze``). Many
user issues stem from incorrectly formatted data, so please describe
your data as clearly as possible.