Settings

In the next step, you need to set the prerequisite key parameters for training the rank model. You need to pass the required parameters in POST v1/rank/settings endpoint for rank settings. All the parameters are depicted in the following table:

name key type value type description
interval List[Enum] Selected enum value Represents the time interval to train ranking model. Available values are weekly, bi-weekly, monthly, quarterly, yearly.
split_size float float Represents split_size to split data. Splitted data would be distributed as X_train, X_test, y_train, y_test and prepare the data for ranking model.
epoch int int Represents the number of epoch for training the ranking model.

You can update the value of settings from PUT v1/rank/settings endpoint and access your rank settings from GET v1/rank/settings endpoint.

Let's have a look at the response of GET v1/rank/settings endpoint

Settings