LARSModel {MachineShop} | R Documentation |
Fit variants of Lasso, and provide the entire sequence of coefficients and fits, starting from zero to the least squares fit.
LARSModel( type = c("lasso", "lar", "forward.stagewise", "stepwise"), trace = FALSE, normalize = TRUE, intercept = TRUE, step = NULL, use.Gram = TRUE )
type |
model type. |
trace |
logical indicating whether status information is printed during the fitting process. |
normalize |
whether to standardize each variable to have unit L2 norm. |
intercept |
whether to include an intercept in the model. |
step |
algorithm step number to use for prediction. May be a decimal
number indicating a fractional distance between steps. If specified, the
maximum number of algorithm steps will be |
use.Gram |
whether to precompute the Gram matrix. |
numeric
step
Default values for the NULL
arguments and further model details can be
found in the source link below.
MLModel
class object.
## Requires prior installation of suggested package lars to run fit(sale_amount ~ ., data = ICHomes, model = LARSModel)