Description Usage Arguments Value
Creates a stacker governor containing the various information and data to run stacked generalization in IHME's MBG framework
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... |
Initialized models. If blank, default versions of earth and gam are created. |
inlist |
logical. Are the models being passed through ... already in a list format? |
data |
data table. Dataset to be machine learned. |
indicator |
character vector. Name of the indicator (and by extension) the column name of the dependant variable |
indicator_family |
character vector. Designates the statistical family that should be modeled. Usually 'binomial' or 'gaussian' |
covariate_layers |
list of raster like objects. A named list of raster like objects of covariates |
fe_equation |
character vector of an equation. The equation specifying the fixed effects portion of the model. It should match with the names of covariate_layers. |
centre_scale |
logical. Determines whether the covariate values are centered/normalized before being returned. Binary variables are ignored. |
time_var |
character vector. Name of the column denoting the time (e.g. period or year) of a given data point |
time_scale |
numeric vector. List of years or times that the time var correlates to. |
weight_col |
character vector. Denotes the column (if applicable) in the dataset that specifies the data weights |
num_fold_cols |
numeric or character. Number of columns/interations for crossfold validation. if a character string, assume it refers to columns already existing in data. They will be renamed to sfold_# |
num_folds |
numeric. The number of folds the data is split on. |
cores |
numeric. The number of cores available for parallel computation |
sge_parameters |
object returned from init_sge. Provides sge parameters to govern submodel computation. If NULL, mclapply is used to run submodels instead |
Stacker governor object
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