Adapted default settings to the ranger() to support
random-over-sampling. Additionally the default settings are modified to the
most common classification settings used in the AMPEL project.
rosranger(
x,
y,
probability = TRUE,
classification = !probability,
min.node.size = if (probability) 10 else 1,
ndups = 1,
...
)matrix/data.frame, feature matrix, see ranger() for
details.
numeric/factor, classification labels, see ranger() for
details.
logical(1), grow probability trees, see ranger()
for details.
logical(1), run classification even if y is
numeric, see ranger() for details.
same as in ranger()
numeric(1), times of duplication of minority class.
further arguments passed to ranger().
ranger object, see ranger() for details.
In contrast to ranger() rusranger() currently just supports binary
classifications.
AMPEL project: Analysis and Reporting System for the Improvement of Patient Safety through Real-Time Integration of Laboratory Findings, https://ampel.care.
ranger()