You have been having quality control problems with a particular subassembly in the plant. You have collected a large number of related features (attributes) about each subassembly produced, such as material properties, suppliers, which machines and line workers were used on the plant floor to assemble it, etc. You want to see if there are any underlying patterns in the data that might help in diagnosing the quality problems. Which ML technique are you most likely to use? Select the correct answer: a. Classification b. Reinforcement Learning c. Regression d. Clustering e. Association Mining