evalTree: Evaluate performance of a conditional inference tree

In environmentalinformatics-marburg/Rsenal: Magic R Functions for Things Various

Evaluate performance of a conditional inference tree

Description

This function evaluates the performance of a so-called conditional inference tree (see ?ctree for details) by calculating various scores, e.g. accuracy, probability of detection, and false alarm ratio. See http://cawcr.gov.au/projects/verification/ for further information.

Usage

evalTree(
  independ = NULL,
  depend,
  data,
  seed = 10L,
  size = 1000L,
  minbucket = 100L,
  n.cores = 1L,
  ...
)

Arguments

independ	numeric. Column index(es) of independent variable(s).
depend	numeric. Column index of dependent variable.
data	data.frame with independent and dependent variables.
seed	integer. Seed required for random number generation, see set.seed.
size	integer. Size of the training sample.
minbucket	integer. Minimum sum of weights in a terminal node.
n.cores	integer. Number of cores for parallel computing.
...	Further arguments passed on to ctree_control.

Value

Model evaluation statistics.

Author(s)

Florian Detsch

See Also

ctree, ctree_control.

environmentalinformatics-marburg/Rsenal documentation built on July 28, 2023, 6:09 a.m.