Calculate thresholds that optimize some statistic (goal) for cues in data
Source:R/fftrees_cuerank.R
fftrees_cuerank.Rdfftrees_cuerank takes an FFTrees object x and
optimizes its goal.threshold (from x$params) for all cues in
newdata (of type data).
Arguments
- x
An
FFTreesobject.- newdata
A dataset with cues to be ranked (as data frame).
- data
The type of data with cues to be ranked (as character:
'train','test', or'dynamic'). Default:data = 'train'.- rounding
integer. An integer value indicating the decimal digit to which non-integer numeric cue thresholds are to be rounded. Default:
rounding = NULL(i.e., no rounding).
Value
A modified FFTrees object (with cue rank information
for the current data type in x$cues$stats).
Details
fftrees_cuerank creates a data frame cuerank_df
that is added to x$cues$stats.
Note that the cue directions and thresholds computed by FFTrees
always predict positive criterion values (i.e., TRUE or signal,
rather than FALSE or noise).
Using these thresholds for negative exits (i.e., for predicting instances of
FALSE or noise) usually requires a reversal (e.g., negating cue direction).
fftrees_cuerank is called (twice) by the fftrees_grow_fan algorithm
to grow fast-and-frugal trees (FFTs).