--- title: XGBoost Reviews meta\_title: 'XGBoost Reviews 2026: Details, Pricing, & Features | G2' meta\_description: Filter 13 reviews by the users' company size, role or industry to find out how XGBoost works for a business like yours. aggregate\_rating: rating\_value: 4.4 review\_count: 13 scale: '5' date\_modified: '2026-08-07' parent\_category: name: Artificial Intelligence url: https://www.g2.com/categories/artificial-intelligence --- # XGBoost Reviews & Product Details XGBoost is an optimized distributed gradient boosting library that is efficient, flexible and portable, it implements machine learning algorithms under the Gradient Boosting framework and provides a parallel tree boosting(also known as GBDT, GBM) that solve many data science problems in a fast and accurate way. * * * Seller [XGBoost](https://www.g2.com/sellers/xgboost) Discussions [XGBoost Community](https://www.g2.com/products/xgboost/discuss) Show More ## Top-Rated Alternatives [ ![Weka](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Weka") Weka 4.3/5(13) ](https://www.g2.com/products/weka/reviews) [ ![Google Cloud TPU](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Google Cloud TPU") Google Cloud TPU 4.5/5(33) ](https://www.g2.com/products/google-cloud-tpu/reviews) [ ![scikit-learn](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "scikit-learn") scikit-learn 4.8/5(60) ](https://www.g2.com/products/scikit-learn/reviews) [ View All Alternatives ](https://www.g2.com/products/xgboost/competitors/alternatives) ## User Insights Average based on 13 real user reviews. [Log in to unlock pricing and user insights](/login) ![GOURI S.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "GOURI S.") GS GOURI S. Technical Lead Data Scientist Mid-Market (51-1000 emp.) 9/11/2021 Business partner of the seller or seller's competitor, not included in G2 scores. "XGBoost for Machine learning models" 4.5/5 What do you like best about XGBoost? 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. Review collected by and hosted on G2.com. What do you dislike about XGBoost? What I don't like about XGBoost is it doesn't handle the outliars in the dataset while machine learning model development. Review collected by and hosted on G2.com. What problems is XGBoost solving and how is that benefiting you? I am using XGBoost for the machine learning model development on a large dataset. It is speedy and provides good results in terms of accuracy and other matrices. Review collected by and hosted on G2.com. Show More Validated ReviewerIncentivizedSource: G2 invite MT Meliksah T. Engineer Enterprise (\> 1000 emp.) 8/17/2019 "The greatest boosting algorithm that existed so far" 4.5/5 What do you like best about XGBoost? 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. Review collected by and hosted on G2.com. What do you dislike about XGBoost? That it is not a part of a bigger package such as Anaconda but we have to install it separately. Also, its greatness comes with the cost of overfitting just like deep neural networks. It learns so good that after hyperparameter tuning it overfits more than other algorithms. Review collected by and hosted on G2.com. Recommendations to others considering XGBoost: Be careful when hyperparameter tuning, it can overfit even though train and test data were separated. Review collected by and hosted on G2.com. What problems is XGBoost solving and how is that benefiting you? I am solving Machine Learning problems with XGBoost. It learns and performs very well both in terms of performance metrics such as accuracy and fscore as well as training time. Review collected by and hosted on G2.com. Show More Current UserValidated ReviewerIncentivizedSource: G2 invite ![Chathuri J.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Chathuri J.") CJ Chathuri J. University Undergaduate Small-Business (50 or fewer emp.) 1/20/2019 "Great algorithm to use for ML training" 5/5 What do you like best about XGBoost? 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. Review collected by and hosted on G2.com. What do you dislike about XGBoost? The underlying concept of the algorithm is somewhat hard to understand at first. And the model has a large number of hyperparameters. Hence, at the beginning, it is difficult to understand the role each hyperparameter plays. But after some reading of the theory of the algorithm etc. the model becomes easy to comprehend and use. Review collected by and hosted on G2.com. Recommendations to others considering XGBoost: Take some time to understand and its concept. Then, it becomes very easy to use XGBoost. Review collected by and hosted on G2.com. What problems is XGBoost solving and how is that benefiting you? I used XGBoost to train models for financial data mostly. But, apart from business problems, I could use the models in ML and data science competitions, I recently participated. Each and every instance, I could achieve high prediction performances from XGBoost. The ability to give high accuracy models is one of the main advantages in XGBoost. Apart from it, it is fast in execution and easy to use. Hence, I believe this algorithm is one of the best tools a data scientist or a ML engineer should possess. Review collected by and hosted on G2.com. Show More Current UserValidated ReviewerIncentivizedSource: G2 invite ![Ajay S.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Ajay S.") AS Ajay S. Senior Software Engineer Small-Business (50 or fewer emp.) 1/24/2019 "One of the powerful Machine Learning algorithm" 4.5/5 What do you like best about XGBoost? - XgBoost is a type of library which you can install on your machine. C++, Java, Python with Sci-kit learn and many more. - It does parallelization tree construction using all CPU cores - The implementation of the algorithm was engineered for the efficiency of computing time and memory resources. - Xgboost ensures the execution speed and model performance - XGBoost internally has parameters for cross-validation, regularization, user-defined objective functions, missing values etc - It helps to reduce overfitting. Review collected by and hosted on G2.com. What do you dislike about XGBoost? There is nothing much I dislike about the Xgboost but for me sometimes tuning the parameters is bit hectic. Review collected by and hosted on G2.com. Recommendations to others considering XGBoost: The main reasons to use XgBoost is its execution speed and increase in model performance. You can solve the classification, regression and ranking problem very easily. There are lot of parameters and user define functions which will surely come in handy. It is always better to try XgBoost first. Review collected by and hosted on G2.com. What problems is XGBoost solving and how is that benefiting you? If you don't know what to do use XgBoost algorithm. I will suggest using XgBoost according to your requirements. I use XgBoost over light GBM because it gives me better results. Mostly in Kaggle competitions, I use such algorithms. Review collected by and hosted on G2.com. Show More Validated ReviewerIncentivizedSource: G2 invite ![Verified User in Research](/assets/icons/anonymous-avatar-purple-4ae1032bdb50ee5682003170c8184aee790d25958bd397abbd384ba52c596a7b.svg "Verified User in Research") GR Verified User in Research Mid-Market (51-1000 emp.) 9/13/2018 "Solid framework for gradient boosting in Python" 3.5/5 What do you like best about XGBoost? 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. Review collected by and hosted on G2.com. What do you dislike about XGBoost? Nothing comes to mind; it is an efficient and easy to use gradient boosting framework. The support for the R version seems a little less than the Python version, but the R version performed well for my needs (relatively small dataset, no multicore processing or need for intense parallelization. Review collected by and hosted on G2.com. What problems is XGBoost solving and how is that benefiting you? We leverage machine learning platforms and statistical methods to evaluate promising social interventions, pulling from many different fields and frameworks. XGBoost is a good implementation of a key technique in machine learning, and it was relatively simple to implement in a public policy context. Review collected by and hosted on G2.com. Show More Validated ReviewerIncentivizedSource: G2 invite ![Verified User in Financial Services](/assets/icons/anonymous-avatar-purple-4ae1032bdb50ee5682003170c8184aee790d25958bd397abbd384ba52c596a7b.svg "Verified User in Financial Services") GF Verified User in Financial Services Enterprise (\> 1000 emp.) 1/24/2019 "XGBoost" 3/5 What do you like best about XGBoost? The application is an easy to use, out-of-the-box software to quickly apply to data prediction problems. It is reliable and fast and portable, making it a versatile tool for machine learning. Review collected by and hosted on G2.com. What do you dislike about XGBoost? There's not much to dislike. It's been pretty popular as a decision tree algorithm and rightly remains a reliable choice for data science applications. Only wished it was developed sooner! Review collected by and hosted on G2.com. What problems is XGBoost solving and how is that benefiting you? Quickly developing a prediction process for data analysis. It has become one of the easiest algorithms to use for quickly prototyping a model. Review collected by and hosted on G2.com. Show More Validated ReviewerIncentivizedSource: G2 invite ![Verified User in Building Materials](/assets/icons/anonymous-avatar-purple-4ae1032bdb50ee5682003170c8184aee790d25958bd397abbd384ba52c596a7b.svg "Verified User in Building Materials") GB Verified User in Building Materials Small-Business (50 or fewer emp.) 1/24/2019 "Awesome " 5/5 What do you like best about XGBoost? The boost is your program makes a better stronger built it makes it easier to build it makes your computer access and easy to use and build your program Review collected by and hosted on G2.com. What do you dislike about XGBoost? None I like everything about it and help me build faster understand and it’s good for programming Review collected by and hosted on G2.com. What problems is XGBoost solving and how is that benefiting you? It solves problems by making your website business faster protect you from anything that like viruses or anything that will affect your business to help it grow Review collected by and hosted on G2.com. Show More Validated ReviewerIncentivizedSource: G2 invite ![Verified User in Computer Software](/assets/icons/anonymous-avatar-purple-4ae1032bdb50ee5682003170c8184aee790d25958bd397abbd384ba52c596a7b.svg "Verified User in Computer Software") GC Verified User in Computer Software Enterprise (\> 1000 emp.) 1/25/2019 "Fast, accurate and efficient library for machine learning" 4/5 What do you like best about XGBoost? XGBoost has better performance than other boosters or gradient functions. Helps return improved accuracy on regression algorithms. Works well on large datasets. Review collected by and hosted on G2.com. What do you dislike about XGBoost? Takes time to train on complex datasets. Requires cross validation for better results. Review collected by and hosted on G2.com. Recommendations to others considering XGBoost: Use XGBoost for scalable applications and predictive analytics. When used appropriately, it delivers better results than contemporaries. Review collected by and hosted on G2.com. What problems is XGBoost solving and how is that benefiting you? Prediction, Analytics, Data mining Review collected by and hosted on G2.com. Show More Validated ReviewerIncentivizedSource: G2 invite ![Verified User in Marketing and Advertising](/assets/icons/anonymous-avatar-purple-4ae1032bdb50ee5682003170c8184aee790d25958bd397abbd384ba52c596a7b.svg "Verified User in Marketing and Advertising") GM Verified User in Marketing and Advertising Enterprise (\> 1000 emp.) 1/22/2019 "ML algorithm good for accuracy" 4/5 What do you like best about XGBoost? it is helpful in building a model that is very accurate in fitting the training. Review collected by and hosted on G2.com. What do you dislike about XGBoost? it can be difficult to preempt overfitting the training data and generalize for testing. Review collected by and hosted on G2.com. What problems is XGBoost solving and how is that benefiting you? marketing research of audience demographics and predicting behavior Review collected by and hosted on G2.com. Show More Validated ReviewerIncentivizedSource: G2 invite ![Verified User in Information Technology and Services](/assets/icons/anonymous-avatar-purple-4ae1032bdb50ee5682003170c8184aee790d25958bd397abbd384ba52c596a7b.svg "Verified User in Information Technology and Services") GI Verified User in Information Technology and Services Small-Business (50 or fewer emp.) 7/26/2018 "Was great for boosting data" 4.5/5 What do you like best about XGBoost? 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. Review collected by and hosted on G2.com. What do you dislike about XGBoost? There was nothing that I disliked about it. Review collected by and hosted on G2.com. Recommendations to others considering XGBoost: I feel that this is a very good method if you are looking to gather all of your data together in a user friendly method and one that can be helpful to your organization. Review collected by and hosted on G2.com. What problems is XGBoost solving and how is that benefiting you? Data and pulling everything together. Review collected by and hosted on G2.com. Show More Validated ReviewerIncentivizedSource: G2 invite ##### Pricing Pricing details for this product isn’t currently available. Visit the vendor’s website to learn more. 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