In Azure Machine Learning, regression is a supervised machine learning technique used to predict continuous numerical values based on input data. According to the Microsoft AI Fundamentals (AI-900) study guide and the Microsoft Learn module "Identify common types of machine learning," regression models are ideal when the goal is to estimate a quantity - such as price, temperature, or, in this case, population size.
In the scenario, the task is to predict the population size of a specific species within a defined area. Population size is a numerical, continuous value that varies depending on multiple factors (like time, environment, and resources). A regression algorithm, such as linear regression or decision tree regression, can be trained on historical data (e.g., species count, area, temperature, food availability) to forecast future population numbers.
Option analysis:
* A. Clustering: Used for unsupervised learning, where the goal is to group similar data points into clusters without predefined labels (e.g., grouping animals by behavior or habitat).
* C. Classification: Used to predict discrete categories or labels (e.g., "endangered" vs. "not endangered"), not numerical values.
Therefore, the correct machine learning type for predicting a continuous value such as population size is Regression.