Process features with no variation

process_novar_feats(features)

Arguments

features

dataframe of features for machine learning

Value

list of two dataframes: features with variability (unprocessed) and without (processed)

Author

Zena Lapp, zenalapp@umich.edu

Examples

process_novar_feats(mikropml::otu_small[, 2:ncol(otu_small)])
#> $novar_feats #> NULL #> #> $var_feats #> # A tibble: 200 x 60 #> Otu00001 Otu00002 Otu00003 Otu00004 Otu00005 Otu00006 Otu00007 Otu00008 #> <int> <int> <int> <int> <int> <int> <int> <int> #> 1 350 268 213 1 208 230 70 230 #> 2 568 1320 13 293 671 103 48 204 #> 3 151 756 802 556 145 271 57 176 #> 4 299 30 1018 0 25 99 75 78 #> 5 1409 174 0 3 2 1136 296 1 #> 6 167 712 213 4 332 534 139 251 #> 7 108 120 160 349 30 971 26 277 #> 8 347 130 131 17 108 263 351 245 #> 9 256 995 871 112 142 137 0 363 #> 10 1648 144 22 249 16 498 129 846 #> # … with 190 more rows, and 52 more variables: Otu00009 <int>, Otu00010 <int>, #> # Otu00011 <int>, Otu00012 <int>, Otu00013 <int>, Otu00014 <int>, #> # Otu00015 <int>, Otu00016 <int>, Otu00017 <int>, Otu00018 <int>, #> # Otu00019 <int>, Otu00020 <int>, Otu00021 <int>, Otu00022 <int>, #> # Otu00023 <int>, Otu00024 <int>, Otu00025 <int>, Otu00026 <int>, #> # Otu00027 <int>, Otu00028 <int>, Otu00029 <int>, Otu00030 <int>, #> # Otu00031 <int>, Otu00032 <int>, Otu00033 <int>, Otu00034 <int>, #> # Otu00035 <int>, Otu00036 <int>, Otu00037 <int>, Otu00038 <int>, #> # Otu00039 <int>, Otu00040 <int>, Otu00041 <int>, Otu00042 <int>, #> # Otu00043 <int>, Otu00044 <int>, Otu00045 <int>, Otu00046 <int>, #> # Otu00047 <int>, Otu00048 <int>, Otu00049 <int>, Otu00050 <int>, #> # Otu00051 <int>, Otu00052 <int>, Otu00053 <int>, Otu00054 <int>, #> # Otu00055 <int>, Otu00056 <int>, Otu00057 <int>, Otu00058 <int>, #> # Otu00059 <int>, Otu00060 <int> #>