A better method was a Boosted Decision Tree (BDT), a type of machine learning algorithm that learned to differentiate between "constant" and "microlensing" light curves.

The FEM-derived permeation datasets were also used to train two AI-based predictive models: a neural network and a gradient boosting decision tree.

Florida State University professor and Gulf Shores resident Dr. David Williams is counting his blessings after he canceled his Thursday lecture just hours before the horrific shooting on FSU's campus.

XGBoost implements gradient-boosted decision trees for scalable tree boosting. By building an ensemble of serially dependent decision trees, XGBoost shows excellent performance across diverse ML tasks ...

In recent years, the clandestine nature of darknet activities has presented an escalating challenge to cybersecurity efforts, necessitating sophisticated methods for the detection and classification ...

Santhanam explained that instead of relying on basic, traditional statistical models, Experian pioneered the use of Gradient-Boosted Decision Trees alongside other machine learning techniques for ...

Today 1,732 students from 39 countries, 42 states, the District of Columbia, and Puerto Rico were offered admission to the Johns Hopkins University undergraduate Class of 2029 in the Regular Decision ...

LightGBM is a high-performance ensemble learning algorithm based on gradient boosting trees (Ke et al., 2017). Its core idea is to iteratively train multiple weak classifiers, where each iteration ...

Xu, B., Wang, Y., Liao, X. and Wang, K. (2023) Efficient Fraud Detection Using Deep Boosting Decision Trees. Decision Support Systems, 175, Article ID 114037.