Lrnr_glmtree: Generalized Linear Model Trees

In tlverse/sl3: Pipelines for Machine Learning and Super Learning

Generalized Linear Model Trees

Description

This learner uses glmtree from partykit to fit recursive partitioning and regression trees in a generalized linear model.

Format

R6Class object.

Value

Learner object with methods for training and prediction. See Lrnr_base for documentation on learners.

Parameters

• formula: An optional object of class formula (or one that can be coerced to that class), which a symbolic description of the generalized linear model to be fit. If not specified a main terms regression model will be supplied, with each covariate included as a term. Please consult glmtree documentation for more information on its use of formula, and for a description on formula syntax consult the details of the glm documentation.

• ...: Other parameters passed to mob_control or glmtree that are not already specified in the sl3_Task. See its documentation for details.

See Also

Other Learners: Custom_chain, Lrnr_HarmonicReg, Lrnr_arima, Lrnr_bartMachine, Lrnr_base, Lrnr_bayesglm, 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_glm_semiparametric, Lrnr_glmnet, Lrnr_glm, Lrnr_grfcate, 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_polspline, 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

Examples

data(cpp_imputed)
# create task for prediction
cpp_task <- sl3_Task$new(
  data = cpp_imputed,
  covariates = c("bmi", "parity", "mage", "sexn"),
  outcome = "haz"
)
# initialization, training, and prediction with the defaults
glmtree_lrnr <- Lrnr_glmtree$new()
glmtree_fit <- glmtree_lrnr$train(cpp_task)
glmtree_preds <- glmtree_fit$predict()

tlverse/sl3 documentation built on Nov. 18, 2024, 12:46 a.m.