Exam AI-900 Topic 1 Question 280 Discussion

The dataset described contains numeric columns (ColumnA through ColumnE). The model's task is to predict the value of ColumnE based on the other numeric columns (A-D). This is a classic regression problem.
According to the Microsoft Azure AI Fundamentals (AI-900) study guide and Microsoft Learn module
"Identify common types of machine learning," a regression model is used when the target variable (the value to predict) is continuous and numeric, such as price, temperature, or-in this case-a numerical value in ColumnE.
Regression models analyze relationships between independent variables (inputs: Columns A-D) and a dependent variable (output: ColumnE) to predict a continuous outcome. Common regression algorithms include linear regression, decision tree regression, and neural network regression.
Option analysis:
* A. Regression: # Correct. Used for predicting numerical, continuous values.
* B. Analysis: # Incorrect. "Analysis" is a general term, not a machine learning model type.
* C. Clustering: # Incorrect. Clustering is unsupervised learning, grouping similar data points, not predicting values.
Therefore, the type of machine learning model used to predict ColumnE (a numeric value) from other numeric columns is Regression, which fits perfectly within Azure's supervised learning models.