Feature selection using random forest

Feature selection using random forest

Usage

ML_RF(object, ylim_min = 0, seed = NULL)

Arguments

object

A dataframe-like data object containing log-metabolite intensity values, with columns corresponding to metabolites and must containing the group column, and the rows corresponding to the samples

ylim_min

the min ylim,default is 0

seed

the seed

Value

test

Examples

library(dplyr)

meta_dat1 <- t(meta_dat) %>%
  as.data.frame() %>%
  dplyr::mutate(group=group)
result_ML_RF <- ML_RF(meta_dat1)

result_ML_RF$p

result_ML_RF$feature_result
#> # A tibble: 122 × 6
#>    normal tumor MeanDecreaseAccuracy MeanDecreaseGini names  raw   
#>     <dbl> <dbl>                <dbl>            <dbl> <chr>  <fct> 
#>  1   4.58  4.50                 4.82            0.576 C00073 C00073
#>  2   4.27  4.57                 4.65            0.624 C05674 C05674
#>  3   4.01  4.41                 4.56            0.597 C02045 C02045
#>  4   3.43  3.42                 3.95            0.380 C00267 C00267
#>  5   3.77  3.41                 3.88            0.366 C00242 C00242
#>  6   3.83  3.17                 3.87            0.483 C00042 C00042
#>  7   2.82  3.64                 3.79            0.524 C00255 C00255
#>  8   3.72  2.37                 3.68            0.529 C02630 C02630
#>  9   3.83  3.06                 3.61            0.373 C00025 C00025
#> 10   3.86  2.57                 3.52            0.435 C00365 C00365
#> # ℹ 112 more rows