Description Usage Arguments Details Value
Perform the Boost algorithm for the algorithms arc-fs, arc-x4, and AdaBoost.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | boostWithArcFs(x, B, data, .procArgs = NULL, metadata = NULL,
initialWeights = rep.int(1, nrow(data))/nrow(data),
analyzePerformance = defaultOOBPerformanceAnalysis,
.boostBackendArgs = NULL)
boostWithArcX4(x, B, data, .procArgs = NULL, metadata = NULL,
initialWeights = rep.int(1, nrow(data))/nrow(data),
analyzePerformance = defaultOOBPerformanceAnalysis,
.boostBackendArgs = NULL)
boostWithAdaBoost(x, B, data, .procArgs = NULL, metadata = NULL,
initialWeights = rep.int(1, nrow(data))/nrow(data),
analyzePerformance = defaultOOBPerformanceAnalysis,
.boostBackendArgs = NULL)
|
x |
a list with entries ' |
B |
number of iterations of boost to perform. |
data |
a data.frame of matrix to act as the learning set. The columns
are assumed to be ordered such that the response variable in the first
column and the remaining columns as the predictors. As a convenience,
|
.procArgs |
a named list of arguments to pass to the estimation
procedure.
If |
initialWeights |
a vector of weights used for the first iteration of the ensemble building phase of Boost. |
analyzePerformance |
a function which accepts an estimator's
predictions and the true responses to said predictions (among other
arguments) and returns a list of values. If no function is provided,
|
metadata |
a named list of additional arguments to be passed to
|
.boostBackendArgs |
a named list of additional arguments to pass to
|
These functions call boost
with the appropriate reweighters,
aggregators, and metadata.
a "boostr
" object that is the output of
boostBackend
.
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