ML.H2O.glm.RdWrapper for an H2O glm estimator. From their discription: Generalized Linear Models (GLM) estimate regression models for outcomes following exponential distributions. In addition to the Gaussian (i.e. normal) distribution, these include Poisson, binomial, and gamma distributions. Each serves a different purpose, and depending on distribution and link function choice, can be used either for prediction or classification.
ML.H2O.glm
An object of class R6ClassGenerator of length 24.
initialize(nfolds = 1, alpha = 0.5, family = "gaussian") Creates a new h2o glm model @param nfold integer (default = 1) specify the number of folds for cross-validation. @param alpha double (default = 0.5) the alpha parameter controls the distribution between the l1 (LASSO) and l2 (ridge regression) penalties. A value of 1.0 for alpha represents LASSO, and an alpha value of 0.0 produces ridge reguression. @param family string (default = "binomial") the family to use for the estimator. Generally this should be binomial (since we are running various logistic regressions). However, if you have a good reason to use a different specification, change it here.