Yahoo Malaysia Web Search

Search results

  1. Dictionary
    regression
    /rɪˈɡrɛʃn/

    noun

    • 1. a return to a former or less developed state: "it is easy to blame unrest on economic regression"
    • 2. a measure of the relation between the mean value of one variable (e.g. output) and corresponding values of other variables (e.g. time and cost).

    More definitions, origin and scrabble points

  2. Jul 2, 2024 · Regression is a statistical method used in finance, investing, and other disciplines that attempts to determine the strength and character of the relationship between a dependent variable and...

  3. In recent decades, new methods have been developed for robust regression, regression involving correlated responses such as time series and growth curves, regression in which the predictor (independent variable) or response variables are curves, images, graphs, or other complex data objects, regression methods accommodating various types of ...

  4. May 20, 2024 · Regression in machine learning is a supervised learning technique employed to forecast the value of the dependent variable for unseen data. It establishes a connection between input features and the target variable, enabling the estimation or prediction of numerical values.

  5. : a functional relationship between two or more correlated variables that is often empirically determined from data and is used especially to predict values of one variable when given values of the others. the regression of y on x is linear.

  6. REGRESSION definition: 1. a return to a previous and less advanced or worse state, condition, or way of behaving: 2. the…. Learn more.

  7. Sep 7, 2023 · Regression analysis is a widely used set of statistical analysis methods for gauging the true impact of various factors on specific facets of a business. These methods help data analysts better understand relationships between variables, make predictions, and decipher intricate patterns within data.

  8. Feb 19, 2020 · Regression models describe the relationship between variables by fitting a line to the observed data. Linear regression models use a straight line, while logistic and nonlinear regression models use a curved line. Regression allows you to estimate how a dependent variable changes as the independent variable (s) change.

  1. Searches related to define regression

    define spurious regression