LightGBM in Python by R4R Team

What Is LightGBM?

-Gradient Boosting is one of the best and most popular machine learning library, which helps developers in building new algorithms by using redefined elementary models and namely decision trees. Therefore, there are special libraries which are designed for fast and efficient implementation of this method.

-These libraries are LightGBM, XGBoost, and CatBoost. All these libraries are competitors that helps in solving a common problem and can be utilized in almost the similar manner.

Features of LightGBM:

-Very fast computation ensures high production efficiency.

-Intuitive, hence makes it user friendly.

-Faster training than many other deep learning libraries.

-Will not produce errors when you consider NaN values and other canonical values.

Where Is LightGBM Used?

-These library provides provide highly scalable, optimized, and fast implementations of gradient boosting, which makes it popular among machine learning developers. Because most of the machine learning full stack developers won machine learning competitions by using these algorithms.




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