xgbtune 1.1.0

Automated XGBoost tunning

XGBTune is a library for automated XGBoost model tuning. Tuning an XGBoost model is as simple as a single function call.

Get Started

from xgbtune import tune_xgb_model

params, round_count = tune_xgb_model(params, x_train, y_train)

Install

XGBTune is available on PyPi and can be installed with pip:

pip install xgbtune

Tuning steps

The tuning is done in the following steps:

• compute best round

• tune max_depth and min_child_weight

• tune gamma

• re-compute best round

• tune subsample and colsample_bytree

• fine tune subsample and colsample_bytree

• tune alpha and lambda

• tune seed

This steps can be repeated several times. By default, two passes are done.