On the Performance of Phase I Dispersion Control Charts under Machine Learning Imputed Data
This study considers two common and powerful machine learning‐based imputation methods; which are the k‐Nearest Neighbors (kNN) and Support Vector Regression (SVR) and compares their effect with the two traditional methods on the performance of the G‐chart designed to monitor the process variability.