Abstract

For situations in which there is labeled data and the prediction objective is clearly defined, supervised machine learning is more appropriate than unsupervised or reinforcement learning because it learns the direct mapping between inputs and known outputs. This approach enhances Six Sigma and quality management by using labeled data for predictive analytics and targeted process optimization.