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Which algorithm is typically used for both regression and classification tasks?

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Question: Which algorithm is typically used for both regression and classification tasks?

Options:

  1. K-Nearest Neighbors
  2. Naive Bayes
  3. Random Forest
  4. Principal Component Analysis

Correct Answer: Random Forest

Solution:

Random Forest can be used for both regression and classification tasks, making it versatile.

Which algorithm is typically used for both regression and classification tasks?

Practice Questions

Q1
Which algorithm is typically used for both regression and classification tasks?
  1. K-Nearest Neighbors
  2. Naive Bayes
  3. Random Forest
  4. Principal Component Analysis

Questions & Step-by-Step Solutions

Which algorithm is typically used for both regression and classification tasks?
  • Step 1: Understand what regression and classification tasks are.
  • Step 2: Know that regression tasks predict continuous values (like prices).
  • Step 3: Know that classification tasks predict categories (like spam or not spam).
  • Step 4: Learn about different algorithms used for these tasks.
  • Step 5: Identify that Random Forest is an algorithm that can handle both types of tasks.
  • Step 6: Conclude that Random Forest is versatile because it can be used for both regression and classification.
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