You have a dataset that contains experimental data for fuel samples. You need to predict the amount of energy that can be obtained from a sample based on its density. Which type of Al workload…

Classification is used to predict a categorical label (e.g., "high energy" or "low energy"), not a specific continuous numerical value.

Clustering is an unsupervised learning technique used to group similar data points together, not to predict a specific output value.

Knowledge mining involves extracting insights from unstructured data, which is a different domain from predicting numerical values from structured experimental data.

Regression is a supervised machine learning technique used to predict a continuous numerical output value (the amount of energy) based on one or more input features (the density of the fuel sample). This involves learning the relationship between inputs and a continuous numerical target.