Returns statistics from double-split cross validation
cross_validate(df, ..., to_center = FALSE, to_scale = FALSE, n_profiles,
distance_metric = "squared_euclidean", linkage = "complete", k = 30,
lower_bound = 2, upper_bound = 9)with two or more columns with continuous variables
unquoted variable names separated by commas
(TRUE or FALSE) for whether to center the raw data with M = 0
Boolean (TRUE or FALSE) for whether to scale the raw data with SD = 1
the number of profiles in the solution to cross-validate; or, the character string "iterate" to perform cross-validation for 2 to 9 profile solutions
Distance metric to use for hierarchical clustering; "squared_euclidean" is default but more options are available (see ?hclust)
Linkage method to use for hierarchical clustering; "complete" is default but more options are available (see ?dist)
the number of iterations
if n_profiles = "iterate", then this is the smallest number of profiles in the range of number of profiles to explore; defaults to 2
if n_profiles = "iterate", then this is the largest number of profiles in the range of number of profiles to explore; defaults to 9
A ggplot2 object
Performs double-split cross validation and returns Cohen's Kappa and percentage agreement statistics.