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What is Supervised learning?

A machine learning approach that trains a model to predict the correct answer from an input, using data made of pairs of inputs and correct answers (labels). It is called regression when the predicted output is a continuous number and classification when it is one of a fixed set of classes. Models such as linear regression, logistic regression, decision trees, support vector machines and neural networks are used. Preparing the labels often takes considerable effort.

Japanese name: 教師あり学習

Supervised learning appears in 2 practice questions across 1 topic, including Machine Learning Basics.

Field: Machine Learning Basics

Try it: questions about Supervised learning

Which of the following supervised learning tasks is a regression task?

  1. ADeciding from the body of an email whether it is spam
  2. BIdentifying which digit from 0 to 9 an image of a handwritten digit shows
  3. CPredicting the price of a house from its floor area, distance to the station and so on
Show answer and explanation

Answer: C. Predicting the price of a house from its floor area, distance to the station and so on

Supervised learning trains a model that predicts an output from an input, using pairs of inputs and correct answers (labels). When the predicted output is a continuous number, the task is called regression; when it is one of a fixed set of classes, it is called classification. A house price is a continuous number, so this is regression. Spam detection is two-class classification, and handwritten digit recognition is ten-class classification.

Supervised learning in the explanations

Questions that mention Supervised learning (2)

  1. Which of the following supervised learning tasks is a regression task?
  2. Which of the following is an example of unsupervised learning?

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Related terms

Unsupervised learning Reinforcement learning Activation function Confusion matrix Convolutional neural network (CNN) Cross-validation Gradient descent k-means clustering Overfitting Precision and recall

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