【发布时间】：2021-01-25 18:19:37
【问题描述】：
我正在尝试使用 Tidymodels 预测 R 中的房地产价格。我正在关注this tutorial。一切都很顺利，直到我尝试对我的测试数据进行预测。
请看下面的代码示例和最后的错误。
我查看了两个类似的问题（here 和 here），但似乎我已经定义了可变角色并为我的工作流程提供了一个未准备好的配方。
# libraries ---------------------------------------------------------------
library(tidymodels)
#> ── Attaching packages ────────────────────────────────────── tidymodels 0.1.2 ──
#> ✓ broom 0.7.3 ✓ recipes 0.1.15
#> ✓ dials 0.0.9 ✓ rsample 0.0.8
#> ✓ dplyr 1.0.3 ✓ tibble 3.0.5
#> ✓ ggplot2 3.3.3 ✓ tidyr 1.1.2
#> ✓ infer 0.5.4 ✓ tune 0.1.2
#> ✓ modeldata 0.1.0 ✓ workflows 0.2.1
#> ✓ parsnip 0.1.5 ✓ yardstick 0.0.7
#> ✓ purrr 0.3.4
#> ── Conflicts ───────────────────────────────────────── tidymodels_conflicts() ──
#> x purrr::discard() masks scales::discard()
#> x dplyr::filter() masks stats::filter()
#> x dplyr::lag() masks stats::lag()
#> x recipes::step() masks stats::step()
library(data.table)
library(purrr)
# data --------------------------------------------------------------------
# 're' means real estate
# I'm using data.table in general. Using tribble below for cleaner data definition.
real_estate_data <- tibble::tribble(
~re_id, ~price_per_sqm_huf_mil, ~district, ~num_room,
"30876343", 0.534722222222222, 1, 3,
"31914489", 0.476119402985075, 1, 1,
"30972289", 0.507352941176471, 1, 2,
"31739730", 0.472972972972973, 1, 3,
"31783137", 0.49875, 2, 3,
"31809435", 0.439705882352941, 2, 2,
"31943408", 0.469117647058824, 2, 3,
"31944348", 0.56231884057971, 2, 1,
"31961146", 0.472972972972973, 3, 3,
"24314388", 0.649550561797753, 3, 2,
"29840270", 0.719178082191781, 3, 3,
"29840429", 0.719178082191781, 3, 3,
"30873484", 0.822857142857143, 4, 3,
"30969673", 0.533802816901408, 4, 3,
"31333120", 0.741511627906977, 4, 3,
"31788730", 0.527142857142857, 4, 2,
"31948441", 0.734848484848485, 5, 2,
"31962350", 0.8, 5, 3,
"31962779", 0.670454545454545, 5, 3,
"31979128", 0.689054054054054, 5, 1
)
real_estate_data <- as.data.table(real_estate_data) %>% .[, district := factor(district)]
# train/test split --------------------------------------------------------
set.seed(123)
re_split <- initial_split(real_estate_data)
re_train <- training(re_split)
re_test <- testing(re_split)
# workflow (w/ recipe) ----------------------------------------------------
re_rec <- recipe(re_train,
formula = price_per_sqm_huf_mil ~ .) %>%
update_role(re_id, new_role = "ID") %>%
step_center(all_numeric(), - district) %>%
step_scale(all_predictors(), all_numeric(), - district) %>%
step_dummy(district) %>%
step_zv(all_predictors())
summary(re_rec)
#> # A tibble: 4 x 4
#> variable type role source
#> <chr> <chr> <chr> <chr>
#> 1 re_id nominal ID original
#> 2 district nominal predictor original
#> 3 num_room numeric predictor original
#> 4 price_per_sqm_huf_mil numeric outcome original
lr_model <-
linear_reg() %>%
set_engine("lm")
re_wflow <-
workflow() %>%
add_model(lr_model) %>%
add_recipe(re_rec)
# model training and prediction -------------------------------------------
re_fit <-
re_wflow %>%
fit(data = re_train)
re_pred <- predict(re_fit, re_test)
#> Error: Can't subset columns that don't exist.
#> x Column `price_per_sqm_huf_mil` doesn't exist.
由reprex package (v0.3.0) 于 2021-01-25 创建
非常感谢！
【问题讨论】：
标签： r tidymodels r-recipes