lowest-level implementation of the fitting of a fuzzy coco model using the hybrid engine

Source: R/engine_hybrid.R

lowest-level implementation of the fitting of a fuzzy coco model using the hybrid engine

fuzzycoco_fit_df_hybrid(
  model,
  x,
  y,
  until = stop_engine_on_first_of(max_generations =
    model$params$global_params$max_generations, max_fitness =
    model$params$global_params$max_fitness),
  verbose = model$verbose,
  progress = TRUE
)

Arguments

model

a Fuzzy Coco model as a fuzzy_coco object

x

the input variables data (usually to fit) as a dataframe

y

the output variables data (usually to fit) as a dataframe

until

function that takes an engine and returns TRUE if and only if the evolution must stop. It is a way for the user to customize the stop conditions of the algorithm.

verbose

whether to be verbose

progress

whether to display the computation progress (using progressr, if available)

Value

a named list as a fuzzy_coco fit object

Examples

 model <- fuzzycoco("regression", example_mtcars()$params)
 fit <- fuzzycoco_fit_df_hybrid(model, mtcars[c("mpg", "hp", "wt")],  mtcars["qsec"])