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XGBoost

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13 reviews
  • 1 profiles
  • 1 categories
Average star rating
4.4
Serving customers since
2008

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Star Rating

9
3
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0

XGBoost Reviews

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Star Rating
9
3
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Verified User in Information Technology and Services
GI
Verified User in Information Technology and Services
07/26/2018
Validated Reviewer
Review source: G2 invite
Incentivized Review

Was great for boosting data

I liked that it was very user friendly and incorporated data in a nice method. I liked the way it worked and it was easy to learn. Their staff was very good at assisting me throughout the process. Any questions that I had were answered immediately and without hesitation. They were kind and flexible to work with. I would definitely recommend.
Verified User in Consumer Goods
GC
Verified User in Consumer Goods
07/26/2018
Validated Reviewer
Review source: G2 invite
Incentivized Review

XGB is the best out of the box model available today

Runs well in basically every situation, handles missing data well, relatively lightweight.
Verified User in Higher Education
GH
Verified User in Higher Education
11/10/2017
Validated Reviewer
Verified Current User
Review source: G2 invite
Incentivized Review

A lot of documentation and great for ML competitions

The documentation makes it really easy to get started after the install. There are plenty of examples online to learn from and is widely regarded in the data community. I have only used xgboost for classification in a Kaggle competition and it made me interested in gradient boosted techniques.

About

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HQ Location:
San Francisco, US

Social

@github

What is XGBoost?

XGBoost (Extreme Gradient Boosting) is an open-source machine learning library that is widely recognized for its efficiency and performance. Designed for speed and performance, XGBoost is a scalable and flexible software framework that supports gradient boosting techniques. It is particularly popular due to its ability to handle large-scale and sparse data, making it a preferred choice for structured or tabular data across a range of classification and regression tasks.XGBoost provides a robust solution for data scientists aiming to achieve state-of-the-art results on predictive modeling challenges. It features several advanced capabilities such as handling missing values, tree pruning, and regularized boosting techniques which help to prevent overfitting and improve model performance.

Details

Year Founded
2008
Website
xgboost.ai