This repository contains a machine learning project focused on predicting global video game sales using regression models like Gradient Boosting and Random Forest. It includes data preprocessing, ...

A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning ...

While there are a number of other libraries out there to help with gradient boosting or other solutions to help train machine learning systems (XGBoost being one), Bilenko argued that the benefit ...

The novel approach to intrusion image prediction explained in this paper uses both Gradient Boosting Feature Selection and Machine Learning Classifiers. Detection of intruders in images is a very ...

The exchange of ideas and opinions on social media is increasingly becoming essential. A vast amount of data is produced by the intense analysis of online social media. The harmony random forest ...

A machine learning gradient boosting regression system, also called a gradient boosting machine (GBM), predicts a single numeric value. A GBM is an ensemble (collection) of simple decision tree ...

Notably, the light gradient boosting machine (LGBM) model outperformed others. As a result, the LGBM model was selected as the predictive tool for assessing Gleevec adherence in patients with GIST.

Compared to existing library implementations of gradient boosting regression, a from-scratch implementation allows much easier customization and integration with other .NET systems. By James McCaffrey ...