3 Questions
Which type of supervised learning problem is when the output variable is a real value?
Regression
What is supervised learning used for?
Recommending items
What are two types of supervised learning?
Classification and Regression
Study Notes
- Supervised learning is a process of an algorithm learning from a training dataset to approximate a mapping function from input to output.
- supervised learning can be broken down into two types: classification and regression.
- Classification problems are when the output variable is a category, such as “red” or “blue”. Regression problems are when the output variable is a real value, such as “dollars” or “weight”.
- There are many different supervised learning algorithms, each suited for a specific type of problem.
- supervised learning is used in a variety of applications, including recommendation and time series prediction.
Test your knowledge of supervised learning and algorithms with this quiz. Explore the concepts of classification, regression, and the various algorithms used in supervised learning.
Make Your Own Quizzes and Flashcards
Convert your notes into interactive study material.
Get started for free
