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This function extends evaluate_sample_k() for any number of samples in a dataset.
evaluate_sample_k()
evaluate_k( data, range = 3:10, samples_col = "Sample", abundance_col = "Abundance", with_plot = FALSE, ... )
A nested data.frame (or a plot) with three indices for each k and for each sample.
a data.frame with, at least, the classification, abundance and sample information for each phylogenetic unit.
The range of values of k to test, default is from 3 to 10.
String with name of column with sample names.
string with name of column with abundance values. Default is "Abundance".
If FALSE (default) returns a vector, but if TRUE will return a plot with the scores.
Extra arguments.
The plot option (with_plot = TRUE) provides centrality metrics for all samples used.
For more details on indices calculation, please see the documentation for evaluate_sample_k(), check_DB(), check_CH() and check_avgSil().
check_DB()
check_CH()
check_avgSil()
evaluate_sample_k(), check_DB(), check_CH(), check_avgSil(), suggest_k()
suggest_k()
# \donttest{ library(dplyr) #' evaluate_k(nice_tidy) # To make simple plot evaluate_k(nice_tidy, range = 4:11, with_plot =TRUE) # }
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