target. All the other parameters are optional.
False. For example, if you want to scale your features, you will have to pass
normalize=Truein the setup function. However, there are three things that will happen by default:
MLflowserver you must run the following command from within the notebook or from the command line. Once the server is initialized, you can track your experiment on
fold_strategy, or number of
foldfor cross-validation. To learn more about all the model validation and selection settings in the setup, see this page.
use_gpu = Truein the setup function. There is no change in the use of the API, however, in some cases, additional libraries have to be installed as they are not installed with the default version or the full version. To learn more about GPU support, see this page.
setupin other modules of PyCaret, see below: