XGBRegressor
Overview
A simple implementation to regression problems using Python 2.7, scikit-learn, and XGBoost. Bulk of code from Complete Guide to Parameter Tuning in XGBoost
XGBRegressor is a general purpose notebook for model training using XGBoost. It contains:
- Functions to preprocess a data file into the necessary train and test set dataframes for XGBoost
- Functions to convert categorical variables into dummies or dense vectors, and convert string values into Python compatible strings
- Additional user functionality that allows notification updates to be sent to a user's chosen Slack channel, so that you know when your model has finished training
- Implementation of sequential hyperparameter grid search via the scikit-learn API
- Implementation of early stopping via the Learning API
Installing XGBoost for Python
Follow instructions here
Resources
Here are some additional resources if you are looking to explore XGBoost and its various APIs more extensively: