r descr_models("cubist_rules", "Cubist")
defaults <- tibble::tibble(parsnip = c("committees", "neighbors", "max_rules"), default = c("1L", "0L", "NA_integer")) param <- cubist_rules() %>% set_engine("Cubist") %>% make_parameter_list(defaults)
This model has r nrow(param)
tuning parameters:
param$item
r uses_extension("cubist_rules", "Cubist", "regression")
library(rules) cubist_rules( committees = integer(1), neighbors = integer(1), max_rules = integer(1) ) %>% set_engine("Cubist") %>% set_mode("regression") %>% translate()
Quinlan R (1992). "Learning with Continuous Classes." Proceedings of the 5th Australian Joint Conference On Artificial Intelligence, pp. 343-348.
Quinlan R (1993)."Combining Instance-Based and Model-Based Learning." Proceedings of the Tenth International Conference on Machine Learning, pp. 236-243.
Kuhn M and Johnson K (2013). Applied Predictive Modeling. Springer.
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