Microsoft Azure AI Fundamentals (AI-900) Practice Exam

Which type of machine learning is best suited for predicting sea level changes over the next decade?

1. Classification

2. Regression

3. Clustering

4. Association

The correct answer is: Regression

The correct choice is regression, as it is particularly well-suited for predicting continuous numerical values, such as sea level changes over a specified period, like the next decade. Regression algorithms analyze the relationship between independent variables (factors that may influence sea level changes, such as temperature, ice melt, etc.) and the dependent variable (the predicted sea level). By modeling these relationships, regression techniques can generate forecasts based on historical data. In this scenario, predicting something like sea level change involves estimating a numerical value, thus making regression the most appropriate approach. It allows for the creation of a model that provides specific predictions based on trends and patterns identified in the data. The other approaches serve different purposes. Classification is used for categorizing data into predefined classes and is not suitable for continuous predictions. Clustering focuses on grouping similar data points together without prior labels and is mainly used for exploratory data analysis rather than making specific predictions. Association, on the other hand, identifies relationships between variables but does not provide predictions about future numerical outcomes. Therefore, for predicting sea level changes, regression is the optimal choice.