boxplot_rel_predicted_train_vs_test: boxplot_rel_predicted_train_vs_test

In shihuang047/crossRanger: Cross-Application of Ranger Models using microbiome data

boxplot_rel_predicted_train_vs_test

Description

Make the boxplot the relative predicted values in both train and test datasets.

Usage

boxplot_rel_predicted_train_vs_test(
  relTrain_data,
  train_target_field = "value",
  train_prefix = "train",
  test_prefix = "test",
  outdir = NULL
)

Arguments

relTrain_data	The output dataframe of calc_rel_predicted.
train_target_field	A string indicating the target field of the training metadata for regression.
train_prefix	The prefix for the dataset in the training data.
test_prefix	The prefix for the dataset in the testing data.
outdir	The output directory.

Author(s)

Shi Huang

Examples

set.seed(123)
train_x <- data.frame(rbind(t(rmultinom(7, 75, c(.201,.5,.02,.18,.099))),
            t(rmultinom(8, 75, c(.201,.4,.12,.18,.099))),
            t(rmultinom(15, 75, c(.011,.3,.22,.18,.289))),
            t(rmultinom(15, 75, c(.091,.2,.32,.18,.209))),
            t(rmultinom(15, 75, c(.001,.1,.42,.18,.299)))))
train_y<- 1:60
test_x <- data.frame(rbind(t(rmultinom(7, 75, c(.201,.5,.02,.18,.099))),
            t(rmultinom(8, 75, c(.201,.4,.12,.18,.099))),
            t(rmultinom(15, 75, c(.011,.3,.22,.18,.289))),
            t(rmultinom(15, 75, c(.091,.2,.32,.18,.209)))))
test_y<- 1:45
train_rf_model<-rf.out.of.bag(train_x, train_y)
predicted_test_y<-predict(train_rf_model$rf.model, test_x)$predictions
relTrain_data<-calc_rel_predicted(train_y, predicted_train_y=train_rf_model$predicted,
                                  train_SampleIDs=NULL,
                                  test_y, predicted_test_y,
                                  test_SampleIDs=NULL)
boxplot_rel_predicted_train_vs_test(relTrain_data)

shihuang047/crossRanger documentation built on Feb. 7, 2023, 10:03 p.m.