calc_rel_predicted: calc_rel_predicted

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

calc_rel_predicted

Description

Calculate the relative predicted values to the spline fit.

Usage

calc_rel_predicted(
  train_y,
  predicted_train_y,
  train_SampleIDs = NULL,
  test_y = NULL,
  predicted_test_y = NULL,
  test_SampleIDs = NULL,
  train_prefix = "train",
  test_prefix = "test",
  train_target_field = "y",
  test_target_field = "y",
  outdir = NULL
)

Arguments

train_y	The numeric labels for training data.
predicted_train_y	The predicted values for training data.
train_SampleIDs	The sample ids in the train data.
test_y	The numeric labels for testing data.
predicted_test_y	The predicted values for test data.
test_SampleIDs	The sample ids in the test data.
train_prefix	The prefix for the dataset in the training data.
test_prefix	The prefix for the dataset in the testing data.
train_target_field	A string indicating the target field of the training metadata for regression.
test_target_field	A string indicating the target field of the testing 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
calc_rel_predicted(train_y, predicted_train_y=train_rf_model$predicted)
calc_rel_predicted(train_y=train_y, predicted_train_y=train_rf_model$predicted,
                   #train_SampleIDs=as.character(1:60),
                   test_y=test_y, predicted_test_y=predicted_test_y,
                   #test_SampleIDs=as.character(1:45),
                   train_target_field="y",  test_target_field="test_y", outdir=NULL)
calc_rel_predicted(train_y=train_y, predicted_train_y=train_rf_model$predicted,
                   train_SampleIDs=as.character(1:60),
                   test_y=test_y, predicted_test_y=predicted_test_y,
                   test_SampleIDs=as.character(1:45),
                   train_target_field="y",  test_target_field="test_y", outdir=NULL)

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