Description Usage Arguments Details Value See Also Examples
View source: R/row_pair_apply.R
One or more fitted heuristics can be passed in. They must all have the same cols_to_fit. If they differ on cols_to_fit, then group them in separate heuristics functions.
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A list of predictPairInternal implementers, e.g. a fitted ttb model. |
Users will generally not use the output directly but instead pass this to rowPairApply.
An object of class heuristics, which implements createFunction. Users will generally not use this directly– rowPairApply will.
rowPairApply
which is what the output of heuristics is
normally passed in to.
heuristicsList
for a version of this function where you can
control the function called (not necessarily predictPairInternal).
predictPairInternal
which must be implemented by heuristics in
order to use them with the heuristics() wrapper function. This only
matters for people implementing their own heuristics.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | # Use one fitted ttbModel with column 1 as criterion and columns 2,3 as
# cues.
data <- cbind(y=c(30,20,10,5), x1=c(1,1,0,0), x2=c(1,1,0,1))
ttb <- ttbModel(data, 1, c(2:3))
rowPairApply(data, heuristics(ttb))
# This outputs ttb's predictions for all 6 row pairs of data.
# (It has 6 row pairs because 4*2/2 = 6.) It gets the predictions
# by calling ttb's predictPairInternal.
# Use the same fitted ttbModel plus a unit weight model with the same
# criterion and cues.
unit <- unitWeightModel(data, 1, c(2,3))
rowPairApply(data, heuristics(ttb, unit))
# This outputs predictions with column names 'ttbModel' and
# 'unitWeightLinearModel'.
# Use the same fitted ttbModel plus another ttbModel that has different
# cols_to_fit. This has to be put in a separate heuristicsList function.
ttb_just_col_3 <- ttbModel(data, 1, c(3), fit_name="ttb3")
rowPairApply(data, heuristics(ttb), heuristics(unit))
# This outputs predictions with column names 'ttbModel' and
# 'ttb3'.
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