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Questions and Answers
Which type of supervised learning problem is when the output variable is a real value?
Which type of supervised learning problem is when the output variable is a real value?
- Classification
- Regression (correct)
- Mapping
- Recommendation
What is supervised learning used for?
What is supervised learning used for?
- Approximating a mapping function
- Classifying data
- Recommending items (correct)
- All of the above
What are two types of supervised learning?
What are two types of supervised learning?
- Classification and Mapping
- Regression and Mapping
- Classification and Regression (correct)
- Recommendation and Time Series Prediction
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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.
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