11.1 Exercise

1. Load the ames dataset
2. Split the data, rsplit
3. Fit a linear model and test it
   1. define model spec
   2. create workflow
   3. fit model
4. calculate the rmse

11.1.1 Solution

library(tidyverse)
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library(tidymodels)
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## ✓ parsnip   0.0.5
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library(AmesHousing)

ames <- AmesHousing::make_ames()

ames_split <- rsample::initial_split(ames)

lm_spec <- parsnip::linear_reg() %>%
  parsnip::set_engine("lm")

lm_wf <- workflows::workflow() %>%
  workflows::add_formula(Sale_Price ~ Gr_Liv_Area) %>%
  workflows::add_model(lm_spec)

lm_split <- lm_wf %>%
  tune::last_fit(ames_split)

lm_split %>% tune::collect_metrics()
## # A tibble: 2 x 3
##   .metric .estimator .estimate
##   <chr>   <chr>          <dbl>
## 1 rmse    standard   56478.   
## 2 rsq     standard       0.435