XG Boost: A Fast and Accurate Open Source Library

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Why is it so hyped?

XG Boost is one of the robust machine learning algorithms today. XG Boost stands for Extreme Gradient Boosted Trees. Boosting is one of the strategies that make use of the concept of ensemble learning. A boosting algorithm combines many simple models to generate the final output. Every tree within the boosting scheme will boost the attributes that led to misclassification from the previous tree. So, we have multiple trees just building on top of each other to correct the previous tree’s errors before it, making it accurate. Because of its accuracy and speed, it is winning many machine learning competitions. Whether it is classification or regression, XG Boost is the best choice.

Major Features

  • Easy to use
  • Computationally efficient
  • Regularized boosting
  • parallel processing
  • Automatic handling of missing values
  • Supports all major programming languages
  • Provides Cross-validation at each iteration
  • Incremental training

Paper: https://xgboost.readthedocs.io/en/latest/

Github:https://github.com/dmlc/xgboost

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