get_info.singular.RdRetrieve some informaiton on the content of a singularize object. Note: always print (cat) information, store the content if you want to programmatically access it.
# S3 method for singular
get_info(x, ...)(invisible) list with two componenents: metrics and standardizations. First slot consists in metrics attributes (corresponding weird info), second slot is a vector containing the names of aggregated standardized derived metrics.
# \dontrun{
library(dplyr)
info <- iris %>% select(-Species) %>% crazyfy() %>% stranger() %>% singularize() %>% get_info()
#> Loading required package: dbscan
#>
#> *** singular object
#>
#> - source metrics
#>
#> knn_k_10_mean
#> weird_method "k-Nearest Neighbour"
#> name "knn"
#> package "FNN"
#> package.source "CRAN"
#> foo "knn.dist"
#> type "distance"
#> sort -1
#> detail "Positive numeric value (distance)"
#> parameters list,2
#> normalizationFunction ?
#> colname "knn_k_10_mean"
#> lof_minPts_5
#> weird_method "Local Outlier Factor"
#> name "lof"
#> package "dbscan"
#> package.source "CRAN"
#> foo "lof"
#> type "lofactor"
#> sort -1
#> detail "Positive numeric value (local outlier factors)"
#> parameters list,1
#> normalizationFunction ?
#> colname "lof_minPts_5"
#>
#>
#> - standardizations
#> N_anom_rank_knn_k_10_mean
#> N_anom_rank_lof_minPts_5
#> N_anom_rank_max
#> N_anom_rank_min
#> N_anom_rank_avg
#> N_anom_rank_damavg
#> N_anom_rank_pruavg
#> N_anom_norm_knn_k_10_mean
#> N_anom_norm_lof_minPts_5
#> N_anom_norm_max
#> N_anom_norm_min
#> N_anom_norm_avg
#> N_anom_norm_damavg
#> N_anom_norm_pruavg
# }