Microsoft Azure AI Fundamentals (AI-900)Describe fundamental principles of machine learning on AzureMedium
A machine learning engineer is developing a model to predict the future sales of a product based on historical sales data, promotional activities, and economic indicators. The model needs to output a specific numerical value representing the predicted sales quantity. Which type of machine learning problem is this?
- AClustering
- BRegression
- CAnomaly Detection
- DClassification
Show answer & explanationAnswer & explanation
Correct answer: B. Regression
Predicting a continuous numerical value, such as sales quantity, is the definition of a regression problem. The output is not a category but a point on a scale.
Why the other options are wrong
- A. Clustering groups similar data points without predefined labels.
- C. Anomaly Detection identifies unusual data points, not predicts continuous values.
- D. Classification predicts discrete categories or labels.
Regression
A supervised machine learning task that involves predicting a continuous numerical value.
- Output is a number (e.g., price, temperature, sales quantity).
- Requires labeled training data.
- Common algorithms include Linear Regression, Decision Tree Regressor, Support Vector Regressor.
Memory trick: Regression predicts 'Real' numbers, like sales figures.