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XGBoost

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

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XGBoost Reviews

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Verified User in Marketing and Advertising
GM
Verified User in Marketing and Advertising
01/22/2019
Validated Reviewer
Review source: G2 invite
Incentivized Review

ML algorithm good for accuracy

it is helpful in building a model that is very accurate in fitting the training.
Chathuri J.
CJ
Chathuri J.
Intern at Forestpin (Pvt) Ltd
01/20/2019
Validated Reviewer
Verified Current User
Review source: G2 invite
Incentivized Review

Great algorithm to use for ML training

I have used XGBoost models for many ML competition problems so far. Every time I could achieve a high accuracy and high performance model through using XGBoost. XGBoost is well known for its better performance and efficient memory management in ML community. Therefore, I highly recommend anyone who is new to the field to learn and use XGBoost. It is must to be in your ML toolkit.
Verified User in Research
GR
Verified User in Research
09/13/2018
Validated Reviewer
Review source: G2 invite
Incentivized Review

Solid framework for gradient boosting in Python

Have used XGBoost multiple times, and it is a very intuitive library that is easy to pick up quickly for the task I had at hand (fairly straightforward gradient boosting task). I only used the package in R form, but have heard good things from colleagues who much more regularly use gradient boosting for predictive projects; XGBoost seems to be the go-to library for boosting for multiple Data Scientists that I work with.

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San Francisco, US

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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