fit the FuzzyCoco model using the dataframe interface

# S3 method for class 'fuzzycoco_model'
fit_xy(
  object,
  x,
  y,
  engine = FUZZY_COCO_HYBRID_ENGINE,
  max_generations = object$params$global_params$max_generations,
  max_fitness = object$params$global_params$max_fitness,
  seed = object$seed,
  verbose = object$verbose,
  ...
)

Arguments

object

the fuzzycoco_model object to fit

x

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

y

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

engine

the fuzzy coco fit engine to use, one of rcpp and hybrid

max_generations

The maximum number of iterations of the algorithm. Each iteration produces a new generation of the rules and membership functions populations.

max_fitness

a stop condition: the iterations stop as soon as a generated fuzzy system fitness reaches that threshold.

seed

the RNG seed to use (to fit the model)

verbose

whether to be verbose

...

Arguments passed on to fuzzycoco_fit_df_hybrid

model: a Fuzzy Coco model as a fuzzy_coco object
progress: whether to display the computation progress (using progressr, if available)
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.

Value

a named list