ensemble models

Tencent Cloud Developer

Apr 12, 2019 · Cloud Computing

Predictive Modeling for Hot Migration in Cloud Computing Using Ensemble Machine Learning

The study introduces a voting ensemble of Random Forest, AdaBoost, and XGBoost to predict hot‑migration success in cloud environments, achieving 97.44% accuracy and cutting timeout failures by roughly 80%, while quantifying feature importance—primarily CPU, network traffic, and memory—to guide proactive resource allocation.