Model Inputs
Model inputs are the predictor and response variables whose relationship is determined by a model fit. Input specifications supported by MachineShop are summarized in the table below.
formula |
Traditional model formula |
matrix |
Design matrix of predictors |
ModelFrame |
Model frame |
recipe |
Preprocessing recipe roles and steps |
Response variable types in the input specifications are defined by the user with the functions and recipe roles:
| Response Functions | BinomialVariate |
DiscreteVariate |
|
factor |
|
matrix |
|
NegBinomialVariate |
|
numeric |
|
ordered |
|
PoissonVariate |
|
Surv |
|
| Recipe Roles | role_binom |
role_surv |
|
Inputs may be combined, selected, or tuned with the following meta-input functions.
ModeledInput |
Input with a prespecified model |
SelectedInput |
Input selection from a candidate set |
TunedInput |
Input tuning over a parameter grid |
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