This learner provides fitting procedures for elastic net models, using the
glmnet
package, using cv.glmnet
to select an
appropriate value of lambda.
Lrnr_glmnet
R6Class
object.
Learner object with methods for training and prediction. See
Lrnr_base
for documentation on learners.
lambda=NULL
A vector of lambda values to compare
type.measure="deviance"
The loss to use when selecting
lambda. Options documented in cv.glmnet
.
nfolds=10
Number of folds to use for internal cross-validation.
alpha=1
The elastic net parameter. 0 is Ridge Regression, 1
is Lasso. Intermediate values are a combination. Documented in
glmnet
.
nlambda=100
The number of lambda values to compare. Comparing
less values will speed up computation, but may decrease statistical
performance. Documented in cv.glmnet
.
use_min=TRUE
If TRUE, use lambda=cv_fit$lambda.min for prediction,
otherwise use lambda=cv_fit$lambda.1se.
the distinction is clarified in cv.glmnet
.
...
Individual learners have their own sets of parameters. Below is a list of shared parameters, implemented by Lrnr_base
, and shared
by all learners.
covariates
A character vector of covariates. The learner will use this to subset the covariates for any specified task
outcome_type
A variable_type
object used to control the outcome_type used by the learner. Overrides the task outcome_type if specified
...
All other parameters should be handled by the invidual learner classes. See the documentation for the learner class you're instantiating
Other Learners: Custom_chain
,
Lrnr_HarmonicReg
, Lrnr_arima
,
Lrnr_bartMachine
, Lrnr_base
,
Lrnr_bilstm
, Lrnr_condensier
,
Lrnr_cv
,
Lrnr_define_interactions
,
Lrnr_expSmooth
,
Lrnr_glm_fast
, Lrnr_glm
,
Lrnr_h2o_grid
, Lrnr_hal9001
,
Lrnr_independent_binomial
,
Lrnr_lstm
, Lrnr_mean
,
Lrnr_nnls
, Lrnr_optim
,
Lrnr_pca
,
Lrnr_pkg_SuperLearner
,
Lrnr_randomForest
,
Lrnr_ranger
, Lrnr_rpart
,
Lrnr_rugarch
, Lrnr_sl
,
Lrnr_solnp_density
,
Lrnr_solnp
,
Lrnr_subset_covariates
,
Lrnr_svm
, Lrnr_tsDyn
,
Lrnr_xgboost
, Pipeline
,
Stack
, define_h2o_X
,
undocumented_learner