What is the main difference between regression and classification in supervised

Practice Questions

Q1
What is the main difference between regression and classification in supervised learning?
  1. Regression predicts continuous values, classification predicts discrete labels
  2. Regression is unsupervised, classification is supervised
  3. Regression uses neural networks, classification does not
  4. There is no difference

Questions & Step-by-Step Solutions

What is the main difference between regression and classification in supervised learning?
  • Step 1: Understand that supervised learning is a type of machine learning where the model is trained on labeled data.
  • Step 2: Know that regression is used when the output is a continuous value, like predicting a person's height or temperature.
  • Step 3: Understand that classification is used when the output is a discrete label, like identifying if an email is spam or not.
  • Step 4: Remember that in regression, the results can be any number within a range, while in classification, the results are specific categories.
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