evalreg {radiant.model}

Evaluate the performance of different regression models

Description

Evaluate the performance of different regression models

Usage

evalreg(
  dataset,
  pred,
  rvar,
  train = "All",
  data_filter = "",
  arr = "",
  rows = NULL,
  envir = parent.frame()
)

Arguments

dataset

Dataset

pred

Predictions or predictors

rvar

Response variable

train

Use data from training ("Training"), test ("Test"), both ("Both"), or all data ("All") to evaluate model evalreg

data_filter

Expression entered in, e.g., Data > View to filter the dataset in Radiant. The expression should be a string (e.g., "training == 1")

arr

Expression to arrange (sort) the data on (e.g., "color, desc(price)")

rows

Rows to select from the specified dataset

envir

Environment to extract data from

Details

Evaluate different regression models based on predictions. See https://radiant-rstats.github.io/docs/model/evalreg.html for an example in Radiant

Value

A list of results

See Also

summary.evalreg to summarize results

plot.evalreg to plot results

Examples

data.frame(price = diamonds$price, pred1 = rnorm(3000), pred2 = diamonds$price) %>%
  evalreg(pred = c("pred1", "pred2"), "price") %>%
  str()