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
)A formula (with a binary criterion variable).
Training data (as data frame).
Data for testing models/prediction (as data frame).
Algorithm for growing FFTs ("ifan" or "dfan") (as character string).
Measure used to select FFTs (as character string).
Measure used to optimize FFT creation (as character string).
Measure used to optimize cue thresholds (as character string).
integer.
string.
integer.
logical.
string.
numeric.
numeric.
list.
list.
string.
string.
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.
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.
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.".
A list of logical elements.
A new FFTrees object.
fftrees_define for defining FFTs;
FFTrees for creating FFTs from and applying them to data.