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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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GOURI S.
GS
GOURI S.
Technical Lead Data Scientist at Comviva
09/11/2021
Validated Reviewer
Review source: G2 invite
Incentivized Review

XGBoost for Machine learning models

The best thing about XGBoost is it provides parallel processing in the machine learning model development; with the help of 4 cores and parallel processing, i was able to develop a machine learning model on 30 Million subscribers in 2 hours.
MT
Meliksah T.
08/17/2019
Validated Reviewer
Verified Current User
Review source: G2 invite
Incentivized Review

The greatest boosting algorithm that existed so far

It's the best performing stand-alone algorithm (not counting deep learning algorithms which is whole another field) famous for winning many online machine learning competitions. It runs fast and performs better than bagging algorithms because it learns from the mistakes of previous tree models that were built within it. It is possible to tune XGBoost for various metrics, too so if you want a high recall, you can do it with the help of GridSearchCV. It is very efficient compared to famous Random Forest algorithm.
Verified User in Computer Software
GC
Verified User in Computer Software
01/25/2019
Validated Reviewer
Review source: G2 invite
Incentivized Review

Fast, accurate and efficient library for machine learning

XGBoost has better performance than other boosters or gradient functions. Helps return improved accuracy on regression algorithms. Works well on large datasets.

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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