View source: R/ranger_reg_plot.R
plot_rel_predicted | R Documentation |
Calculate the relative predicted values to the spline fit in the training data.
plot_rel_predicted( relTrain_data, prefix = "train", target_field = "value", outdir = NULL )
relTrain_data |
The output dataframe of |
prefix |
The prefix of a train dataset. |
target_field |
A string indicating the target field in the metadata for regression. |
outdir |
The output directory. |
Shi Huang
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)
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