Khái niệm cốt lõi
Utilizing explainability techniques to enhance machine learning models for quality prediction in manufacturing processes.
Thống kê
"The Gradient Boosting Regression model yielded an error rate of 4.58%."
"By choosing only the top 20% of features deemed most critical, we enhanced the MAPE from approximately 4.58 to 4.4."
Trích dẫn
"Explainability techniques are crucial in unraveling the complex prediction mechanisms embedded within ML models."
"Feature selection based on explainability methods can enhance model performance and reduce manufacturing costs."