Question

When the output is one of a finite set of values (such as sunny/cloudy/rainy or true/false), the learning problem is known as:

• A. Classification
• B. Clustering
• C. Regression
• D. Optimization

Hint:

Classification problems involve predicting categorical outcomes from a set of predefined classes.

Answer 1

The Correct Option is A

Step 1: Define the Learning Problem.
Classification is a supervised learning task where the objective is to predict a categorical output, which is a value from a finite set, such as "sunny" or "rainy."

Step 2: Evaluate the Available Options.
- (A) Classification: This option is accurate, as classification is applied when the desired output is categorical.
- (B) Clustering: This option is incorrect. Clustering is an unsupervised method for grouping data points based on similarity and does not involve predicting categorical outcomes.
- (C) Regression: This option is incorrect. Regression is used for predicting continuous numerical values, not categorical ones.
- (D) Optimization: This option is incorrect. Optimization aims to find the most efficient solution to a problem and is not specifically concerned with categorizing data.

Step 3: State the Final Decision.
The correct answer is (A) Classification.