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  2. Elastic net regularization - Wikipedia

    en.wikipedia.org/wiki/Elastic_net_regularization

    "Glmnet: Lasso and elastic-net regularized generalized linear models" is a software which is implemented as an R source package and as a MATLAB toolbox. [ 10 ] [ 11 ] This includes fast algorithms for estimation of generalized linear models with ℓ 1 (the lasso), ℓ 2 (ridge regression) and mixtures of the two penalties (the elastic net ...

  3. Generalized additive model for location, scale and shape

    en.wikipedia.org/wiki/Generalized_additive_model...

    The generalized additive model for location, scale and shape (GAMLSS) is a semiparametric regression model in which a parametric statistical distribution is assumed for the response (target) variable but the parameters of this distribution can vary according to explanatory variables.

  4. Generalized chi-squared distribution - Wikipedia

    en.wikipedia.org/wiki/Generalized_chi-squared...

    The probability density, cumulative distribution, and inverse cumulative distribution functions of a generalized chi-squared variable do not have simple closed-form expressions. But there exist several methods to compute them numerically: Ruben's method, [ 7 ] Imhof's method, [ 8 ] IFFT method, [ 6 ] ray method, [ 6 ] and ellipse approximation.

  5. Generalized linear mixed model - Wikipedia

    en.wikipedia.org/wiki/Generalized_linear_mixed_model

    MATLAB also provides a fitglme function to fit generalized linear mixed model models. The Python Statsmodels package supports binomial and poisson implementations. [14] The Julia package MixedModels.jl provides a function called GeneralizedLinearMixedModel that fits a generalized linear mixed model to provided data. [15]

  6. Generalised logistic function - Wikipedia

    en.wikipedia.org/wiki/Generalised_logistic_function

    The generalized logistic function or curve is an extension of the logistic or sigmoid functions. Originally developed for growth modelling, it allows for more flexible S-shaped curves. The function is sometimes named Richards's curve after F. J. Richards, who proposed the general form for the family of models in 1959.

  7. Relief (feature selection) - Wikipedia

    en.wikipedia.org/wiki/Relief_(feature_selection)

    Relief is an algorithm developed by Kira and Rendell in 1992 that takes a filter-method approach to feature selection that is notably sensitive to feature interactions. [1] [2] It was originally designed for application to binary classification problems with discrete or numerical features.

  8. General linear model - Wikipedia

    en.wikipedia.org/wiki/General_linear_model

    generalized linear mixed model (GLMM), generalized estimating equations (GEE) R package and function lm() in stats package (base R) glm() in stats package (base R) Matlab function mvregress() glmfit() SAS procedures PROC GLM, PROC REG: PROC GENMOD, PROC LOGISTIC (for binary & ordered or unordered categorical outcomes) Stata command regress glm ...

  9. Generalized method of moments - Wikipedia

    en.wikipedia.org/wiki/Generalized_method_of_moments

    In econometrics and statistics, the generalized method of moments (GMM) is a generic method for estimating parameters in statistical models.Usually it is applied in the context of semiparametric models, where the parameter of interest is finite-dimensional, whereas the full shape of the data's distribution function may not be known, and therefore maximum likelihood estimation is not applicable.