What type of learning does Support Vector Machines primarily utilize?

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Question: What type of learning does Support Vector Machines primarily utilize?

Options:

Correct Answer: Supervised learning

Solution:

Support Vector Machines are a supervised learning algorithm, as they require labeled training data to learn the decision boundary.

What type of learning does Support Vector Machines primarily utilize?

What type of learning does Support Vector Machines primarily utilize?

Step 1: Understand what Support Vector Machines (SVM) are. They are a type of algorithm used in machine learning.
Step 2: Learn about the two main types of learning in machine learning: supervised and unsupervised learning.
Step 3: Recognize that supervised learning means the algorithm learns from labeled data, where each example has a known output.
Step 4: Identify that Support Vector Machines need labeled training data to create a model that can classify new data.
Step 5: Conclude that since SVM requires labeled data to learn, it is classified as a supervised learning algorithm.

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