In supervised learning, what is the primary goal of regression algorithms?

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Question: In supervised learning, what is the primary goal of regression algorithms?

Options:

Correct Answer: To predict continuous outcomes

Solution:

The primary goal of regression algorithms in supervised learning is to predict continuous outcomes based on input features.

In supervised learning, what is the primary goal of regression algorithms?

In supervised learning, what is the primary goal of regression algorithms?

Step 1: Understand that supervised learning is a type of machine learning where we train a model using labeled data.
Step 2: Know that regression algorithms are a specific type of supervised learning.
Step 3: Recognize that the main task of regression algorithms is to make predictions.
Step 4: Identify that these predictions are for continuous outcomes, which means they can take any value within a range (like height, weight, or temperature).
Step 5: Conclude that regression algorithms use input features (data points) to predict these continuous outcomes.

Regression Algorithms – Regression algorithms are used in supervised learning to model the relationship between input features and continuous output variables.