rosranger: ROS ranger

In ampel-leipzig/rusranger: Modified ranger implementation to support random-under-sampling

ROS ranger

Description

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.

Usage

rosranger(
  x,
  y,
  probability = TRUE,
  classification = !probability,
  min.node.size = if (probability) 10 else 1,
  ndups = 1,
  ...
)

Arguments

x	matrix/data.frame, feature matrix, see ranger() for details.
y	numeric/factor, classification labels, see ranger() for details.
probability	logical(1), grow probability trees, see ranger() for details.
classification	logical(1), run classification even if y is numeric, see ranger() for details.
min.node.size,	same as in ranger()
ndups	numeric(1), times of duplication of minority class.
...	further arguments passed to ranger().

Details

In contrast to ranger() rusranger() currently just supports binary classifications.

Value

ranger object, see ranger() for details.

References

AMPEL project: Analysis and Reporting System for the Improvement of Patient Safety through Real-Time Integration of Laboratory Findings, https://ampel.care.

See Also

ranger()

ampel-leipzig/rusranger documentation built on April 28, 2022, 3:22 a.m.