evalreg: Evaluate the performance of different regression models

Description Usage Arguments Details Value See Also Examples

View source: R/evalreg.R

Description

Evaluate the performance of different regression models

Usage

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evalreg(dataset, pred, rvar, train = "All", data_filter = "")

Arguments

dataset

Dataset

pred

Predictions or predictors

rvar

Response variable

train

Use data from training ("Training"), validation ("Validation"), 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")

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

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

radiant.model documentation built on June 15, 2018, 9:13 a.m.