plot_rel_predicted: plot_rel_predicted

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

plot_rel_predicted

Description

Calculate the relative predicted values to the spline fit in the training data.

Usage

plot_rel_predicted(
  relTrain_data,
  prefix = "train",
  target_field = "value",
  outdir = NULL
)

Arguments

relTrain_data	The output dataframe of calc_rel_predicted.
prefix	The prefix of a train dataset.
target_field	A string indicating the target field in the metadata for regression.
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, train_rf_model$predicted, test_y, predicted_test_y)
plot_rel_predicted(relTrain_data)

shihuang047/crossRanger documentation built on Nov. 8, 2024, 2:49 a.m.