Engineering
a year ago

Revolutionizing Energy Efficiency: Xgboost Model Outperforms RNN in Load Monitoring

Grid Search Based Hyperparameter Optimization for Machine Learning Based Non-Intrusive Load Monitoring
Burak Cem Sayılar, Oğuzhan Ceylan

Paper Summary

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XGBoost Dominates Machine Learning Algorithms with Grid Search Optimization

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Researchers developed two machine learning models, Xgboost and Recurrent Neural Network, to solve the Non-Intrusive Load Monitoring problem. They used a publicly available dataset and implemented hyperparameter optimization through grid search to improve performance. The Xgboost model outperformed the RNN model, resulting in increased numerical accuracy.