Description Format Value Parameters See Also
This learner provides fitting procedures for an adaptive regression procedure
using piecewise linear splines to model the response, using the function
polymars
or polyclass
from
the polspline
package as appropriate.
R6Class
object.
Learner object with methods for training and prediction. See
Lrnr_base
for documentation on learners.
cv
The number of cross-validation folds to be used in
evaluating the sequence of fit models. This is only passed to
polyclass
for binary/categorical outcomes.
...
Other parameters passed to either
polymars
or polyclass
.
See their documentation for details.
Other Learners:
Custom_chain
,
Lrnr_HarmonicReg
,
Lrnr_arima
,
Lrnr_bartMachine
,
Lrnr_base
,
Lrnr_bayesglm
,
Lrnr_bilstm
,
Lrnr_caret
,
Lrnr_cv_selector
,
Lrnr_cv
,
Lrnr_dbarts
,
Lrnr_define_interactions
,
Lrnr_density_discretize
,
Lrnr_density_hse
,
Lrnr_density_semiparametric
,
Lrnr_earth
,
Lrnr_expSmooth
,
Lrnr_gam
,
Lrnr_ga
,
Lrnr_gbm
,
Lrnr_glm_fast
,
Lrnr_glmnet
,
Lrnr_glm
,
Lrnr_grf
,
Lrnr_gru_keras
,
Lrnr_gts
,
Lrnr_h2o_grid
,
Lrnr_hal9001
,
Lrnr_haldensify
,
Lrnr_hts
,
Lrnr_independent_binomial
,
Lrnr_lightgbm
,
Lrnr_lstm_keras
,
Lrnr_mean
,
Lrnr_multiple_ts
,
Lrnr_multivariate
,
Lrnr_nnet
,
Lrnr_nnls
,
Lrnr_optim
,
Lrnr_pca
,
Lrnr_pkg_SuperLearner
,
Lrnr_pooled_hazards
,
Lrnr_randomForest
,
Lrnr_ranger
,
Lrnr_revere_task
,
Lrnr_rpart
,
Lrnr_rugarch
,
Lrnr_screener_augment
,
Lrnr_screener_coefs
,
Lrnr_screener_correlation
,
Lrnr_screener_importance
,
Lrnr_sl
,
Lrnr_solnp_density
,
Lrnr_solnp
,
Lrnr_stratified
,
Lrnr_subset_covariates
,
Lrnr_svm
,
Lrnr_tsDyn
,
Lrnr_ts_weights
,
Lrnr_xgboost
,
Pipeline
,
Stack
,
define_h2o_X()
,
undocumented_learner
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.