XGBoost
When using auto_record()
with XGBoost models, the following information is saved:
- Hyper-parameters: Includes parameters returned by
xgboost.Booster.save_config()
. Check the XGBoost documentation for more details. - Metrics: Records epoch-time versus epoch and any custom metrics logged by the user. If no metrics are specified, XGBoost logs loss on the specified validation sets by default.
To use auto_record
with XGBoost in MarkovML, provide the following:
name
: XGBoost model name.notes
: Notes for future reference. (optional)project_id
: Project ID of the Project you will work on.model_class
: Define Markov model class.
Sample Code
import markov
import xgboos
MODEL_NAME = "My Test XGBoost Model"
markov.xgboost.auto_record(
name=MODEL_NAME,
notes="Testing XGBoost Auto Record with MarkovML",
project_id="some_project_id",
model_class=markov.ModelClass.CLASSIFICATION
)
# Continue creating the XGBoost model and training
Updated about 2 months ago
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