Create an ensemble or comparison table of new MachineLearning and/or Regression models
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formula 
A formula of the form 
data 
A 
subset 
An optional vector specifying a subset of observations to be
used in the fitting process, or, the name of a variable in 
weights 
An optional vector of sampling weights, or the
name of a variable in 
evaluation.subset 
An optional vector specifying a subset of observations to be used for evaluating the models. If not specified, models will only be compared on the training data. If models are not trained on the whole sample To evaluate on the whole sample, a subset must still be specified. 
missing 
How missing data is to be treated. Options:

show.labels 
Shows the variable labels, as opposed to the labels, in the outputs, where a variables label is an attribute (e.g., attr(foo, "label")). 
seed 
The random number seed. 
models.args 
A 
compare.only 
Logical; whether to just produce a table comparing the models or additionally combine them to make a new ensemble model. 
optimal.ensemble 
Logical; whether to find the ensemble with the best accuracy or
rsquared, calculated on the 
output 
If 
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