add_predictions: Add predictions to a data frame

In modelr: Modelling Functions that Work with the Pipe

Add predictions to a data frame

Description

Add predictions to a data frame

Usage

add_predictions(data, model, var = "pred", type = NULL)

spread_predictions(data, ..., type = NULL)

gather_predictions(data, ..., .pred = "pred", .model = "model", type = NULL)

Arguments

data	A data frame used to generate the predictions.
model	add_predictions takes a single model;
var	The name of the output column, default value is pred
type	Prediction type, passed on to stats::predict(). Consult predict() documentation for given model to determine valid values.
...	gather_predictions and spread_predictions take multiple models. The name will be taken from either the argument name of the name of the model.
.pred, .model	The variable names used by gather_predictions.

Value

A data frame. add_prediction adds a single new column, with default name pred, to the input data. spread_predictions adds one column for each model. gather_predictions adds two columns .model and .pred, and repeats the input rows for each model.

Examples

df <- tibble::tibble(
  x = sort(runif(100)),
  y = 5 * x + 0.5 * x ^ 2 + 3 + rnorm(length(x))
)
plot(df)

m1 <- lm(y ~ x, data = df)
grid <- data.frame(x = seq(0, 1, length = 10))
grid %>% add_predictions(m1)

m2 <- lm(y ~ poly(x, 2), data = df)
grid %>% spread_predictions(m1, m2)
grid %>% gather_predictions(m1, m2)

modelr documentation built on March 31, 2023, 5:20 p.m.