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Data Science & Analytics vocabulary · Modelling and Machine Learning

Regression

Meaning in data science & analytics, with examples

/rɪˈɡreʃən/nounCommon term

In data science & analytics, regression means: A family of methods that model how a numeric outcome, such as sales or price, depends on one or more input variables, used to estimate effects or make predictions.

In Turkish: regresyon, regresyon analizi

How it is used

You run, fit or interpret a regression. Linear regression is the classic example; logistic regression, despite its name, is used for classification. In machine learning, 'a regression problem' means predicting a number rather than a category.

Example sentences

  1. We ran a regression of sales on price and advertising spend.

  2. Predicting delivery time is a regression problem, not a classification one.

Common collocations

  • linear regression
  • logistic regression
  • run a regression
  • regression model
  • regression coefficient
  • classificationA type of modelling task in which the model predicts which category something belongs to, such as spam or not spam, or which product a review is about.
  • modelA mathematical representation of a real process, built from data, that is used to explain relationships or to make predictions about new cases.
  • correlationA relationship between two variables in which they tend to change together, often measured by a coefficient from -1 to 1, where 0 means no linear relationship.
  • target variableThe value a model is trained to predict, such as whether a customer will churn or how much they will spend; also called the label or dependent variable.

This word in other fields

The same English word can have a different meaning in another field:

More terms: Modelling and Machine Learning

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