tna (version 1.2.0)

reliability: Assess Model Reliability

Description

Performs reliability analysis and outputs a concise summary of key metrics. The results can also be visualized.

Usage

reliability(x, ...)
# S3 method for tna
reliability(
  x,
  types = "relative",
  split = 0.5,
  iter = 1000,
  scaling = "none",
  ...
)

Value

A tna_reliability object.

Arguments

x

A tna object.

...

Ignored.

types

A character vector giving the model types to fit. See build_model() for available options.

split

A numeric value between 0 and 1 specifying the proportion of data for the split. The default is 0.5 for an even split.

iter

An integer specifying number of iterations (splits). The default is 1000.

scaling

See compare().

See Also

Validation functions bootstrap(), deprune(), estimate_cs(), permutation_test(), permutation_test.group_tna(), plot.group_tna_bootstrap(), plot.group_tna_permutation(), plot.group_tna_stability(), plot.tna_bootstrap(), plot.tna_permutation(), plot.tna_reliability(), plot.tna_stability(), print.group_tna_bootstrap(), print.group_tna_permutation(), print.group_tna_stability(), print.summary.group_tna_bootstrap(), print.summary.tna_bootstrap(), print.tna_bootstrap(), print.tna_clustering(), print.tna_permutation(), print.tna_reliability(), print.tna_stability(), prune(), pruning_details(), reprune(), summary.group_tna_bootstrap(), summary.tna_bootstrap()

Examples

# Small number of iterations for CRAN
model <- tna(engagement)
rel <- reliability(model, iter = 20)