Created by: jonmhong
What is this Python project?
XGBoost is a gradient boosting library. It's one of the most popular GB libraries used among Kaggle users because it's yielded some of the highest scores. And its also a favorite with some of the champions. Here's an example of its use with an Otto dataset: https://www.kaggle.com/tqchen/otto-group-product-classification-challenge/understanding-xgboost-model-on-otto-data Here is a Kaggle first place team winner, showing their love for it: http://blog.kaggle.com/2015/12/03/dato-winners-interview-1st-place-mad-professors/ Describe features.
What's the difference between this Python project and similar ones?
This library is solely for gradient boosting. This resolves issue #821 (closed). Enumerate comparisons.
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