fftrees_create creates an FFTrees object.

fftrees_create is called internally by the main FFTrees function. Its main purpose is to verify and store various parameters (e.g., to denote algorithms, goals, thresholds) to be used in maximization processes and for evaluation purposes (e.g., sens.w and cost values).

fftrees_create(
  formula = NULL,
  data = NULL,
  data.test = NULL,
  algorithm = NULL,
  goal = NULL,
  goal.chase = NULL,
  goal.threshold = NULL,
  max.levels = NULL,
  numthresh.method = NULL,
  numthresh.n = NULL,
  repeat.cues = NULL,
  stopping.rule = NULL,
  stopping.par = NULL,
  sens.w = NULL,
  cost.outcomes = NULL,
  cost.cues = NULL,
  main = NULL,
  decision.labels = NULL,
  my.goal = NULL,
  my.goal.fun = NULL,
  my.tree = NULL,
  quiet = NULL
)

Arguments

formula

A formula (with a binary criterion variable).

data

Training data (as data frame).

data.test

Data for testing models/prediction (as data frame).

algorithm

Algorithm for growing FFTs ("ifan" or "dfan") (as character string).

goal

Measure used to select FFTs (as character string).

goal.chase

Measure used to optimize FFT creation (as character string).

goal.threshold

Measure used to optimize cue thresholds (as character string).

max.levels

integer.

numthresh.method

string.

numthresh.n

integer.

repeat.cues

logical.

stopping.rule

string.

stopping.par

numeric.

sens.w

numeric.

cost.outcomes

list.

cost.cues

list.

main

string.

decision.labels

string.

my.goal

The name of an optimization measure defined by my.goal.fun (as a character string). Example: my.goal = "my_acc" (see my.goal.fun for corresponding function). Default: my.goal = NULL.

my.goal.fun

The definition of an outcome measure to optimize, defined as a function of the frequency counts of the 4 basic classification outcomes hi, fa, mi, cr (i.e., an R function with 4 arguments hi, fa, mi, cr). Example: my.goal.fun = function(hi, fa, mi, cr){(hi + cr)/(hi + fa + mi + cr)} (i.e., accuracy). Default: my.goal.fun = NULL.

my.tree

A verbal description of an FFT, i.e., an "FFT in words" (as character string). For example, my.tree = "If age > 20, predict TRUE. If sex = {m}, predict FALSE. Otherwise, predict TRUE.".

quiet

A list of logical elements.

Value

A new FFTrees object.

See also

fftrees_define for defining FFTs; FFTrees for creating FFTs from and applying them to data.