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  2. Coefficient of determination - Wikipedia

    en.wikipedia.org/wiki/Coefficient_of_determination

    Ordinary least squares regression of Okun's law.Since the regression line does not miss any of the points by very much, the R 2 of the regression is relatively high.. In statistics, the coefficient of determination, denoted R 2 or r 2 and pronounced "R squared", is the proportion of the variation in the dependent variable that is predictable from the independent variable(s).

  3. Non-negative least squares - Wikipedia

    en.wikipedia.org/wiki/Non-negative_least_squares

    In mathematical optimization, the problem of non-negative least squares (NNLS) is a type of constrained least squares problem where the coefficients are not allowed to become negative. That is, given a matrix A and a (column) vector of response variables y , the goal is to find [ 1 ]

  4. Symbolic regression - Wikipedia

    en.wikipedia.org/wiki/Symbolic_regression

    This is an example of divide and conquer, which reduces the size of the problem to be more manageable. AI Feynman also transforms the inputs and outputs of the mystery function in order to produce a new function which can be solved with other techniques, and performs dimensional analysis to reduce the number of independent variables involved.

  5. Pseudo-R-squared - Wikipedia

    en.wikipedia.org/wiki/Pseudo-R-squared

    R 2 L is given by Cohen: [1] =. This is the most analogous index to the squared multiple correlations in linear regression. [3] It represents the proportional reduction in the deviance wherein the deviance is treated as a measure of variation analogous but not identical to the variance in linear regression analysis. [3]

  6. scikit-learn - Wikipedia

    en.wikipedia.org/wiki/Scikit-learn

    scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...

  7. Evaluation of binary classifiers - Wikipedia

    en.wikipedia.org/wiki/Evaluation_of_binary...

    An F-score is a combination of the precision and the recall, providing a single score. There is a one-parameter family of statistics, with parameter β, which determines the relative weights of precision and recall. The traditional or balanced F-score is the harmonic mean of precision and recall:

  8. Multivariate adaptive regression spline - Wikipedia

    en.wikipedia.org/wiki/Multivariate_adaptive...

    For example, each line in the formula for ozone above is one basis function multiplied by its coefficient. Each basis function takes one of the following three forms: 1) a constant 1. There is just one such term, the intercept. In the ozone formula above, the intercept term is 5.2. 2) a hinge function.

  9. Ridge regression - Wikipedia

    en.wikipedia.org/wiki/Ridge_regression

    Ridge regression is a method of estimating the coefficients of multiple-regression models in scenarios where the independent variables are highly correlated. [1] It has been used in many fields including econometrics, chemistry, and engineering. [2]