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:
Show Hint
- Classification
- Clustering
- Regression
- Optimization
The Correct Option is A
Solution and Explanation
Step 1: Understanding the learning problems.
Classification is a supervised learning problem where the output is categorical, meaning it takes on a finite set of values, such as "sunny" or "rainy."
Step 2: Analysis of options.
- (A) Classification: Correct, classification is used when the output is categorical.
- (B) Clustering: Incorrect, clustering is an unsupervised technique used for grouping similar data points, not for categorical output.
- (C) Regression: Incorrect, regression deals with predicting continuous values, not categorical ones.
- (D) Optimization: Incorrect, optimization focuses on finding the best solution to a problem but does not specifically involve categorizing data.
Step 3: Conclusion.
The correct answer is (A) Classification.
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