What is a regression model?
Informally, a model that generates a numerical prediction.
regression model explained in plain English
Informally, a model that generates a numerical prediction. (In contrast, a classification model generates a class prediction.) For example, the following are all regression models: - A model that predicts a certain house's value in Euros, such as 423,000. - A model that predicts a certain tree's life expectancy in years, such as 23.2. - A model that predicts the amount of rain in inches that will fall in a certain city over the next six hours, such as 0.18. Two common types of regression models are: - Linear regression, which finds the line that best fits label values to features. - Logistic regression, which generates a probability between 0.0 and 1.0 that a system typically then maps to a class prediction. Not every model that outputs numerical predictions is a regression model. In some cases, a numeric prediction is really just a classification model that happens to have numeric class names. For example, a model that predicts a numeric postal code is a classification model, not a regression model.
Example
Practitioners refer to regression model when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.
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