data
and target
. All the other parameters are optional.silent=True
in the setup to run it without any interruption. clustering
, anomaly detection
or NLP
.True
or False
. For example, if you want to scale your features, you will have to pass normalize=True
in the setup function. However, there are three things that will happen by default:MLflow
server 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 https://localhost:5000
.train_size
, fold_strategy
, or number of fold
for cross-validation. To learn more about all the model validation and selection settings in the setup, see this page.use_gpu = True
in 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.setup
in other modules of PyCaret, see below:setup
function twice in the same script, it will overwrite the previous experiment. PyCaret next major release will include a new object-oriented API that will make it possible to create multiple instances through class instances.