I have data located here: data_tbl.xlsx I cannot upload data here or don't know how.
The issue is that I am getting an error when trying to fit my training data to a workflow. I don't understand the issue, nor why I am getting it.
Here is my juiced data (recipe_num_only recipe): juiced_recipe.xlsx
Here is my splits object:
splits <- initial_time_split(
data_final_tbl
, prop = 0.8
, cumulative = TRUE
)
Here are my recipes (the one in question is recipe_num_only)
# Features ----------------------------------------------------------------
recipe_base <- recipe(value ~ ., data = training(splits))
recipe_date <- recipe_base %>%
step_timeseries_signature(date_col) %>%
step_rm(matches("(iso$)|(xts$)|(hour)|(min)|(sec)|(am.pm)")) %>%
step_normalize(contains("index.num"), contains("date_col_year"))
recipe_fourier <- recipe_date %>%
step_dummy(all_nominal_predictors(), one_hot = TRUE) %>%
step_fourier(date_col, period = 365/12, K = 1) %>%
step_YeoJohnson(value, limits = c(0,1))
recipe_fourier_final <- recipe_fourier %>%
step_nzv(all_predictors())
recipe_pca <- recipe_base %>%
step_timeseries_signature(date_col) %>%
step_rm(matches("(iso$)|(xts$)|(hour)|(min)|(sec)|(am.pm)")) %>%
step_dummy(all_nominal_predictors(), one_hot = TRUE) %>%
step_normalize(value) %>%
step_fourier(date_col, period = 365/52, K = 1) %>%
step_normalize(all_numeric_predictors()) %>%
step_nzv(all_predictors()) %>%
step_pca(
all_numeric_predictors(), -date_col_index.num
, threshold = .95
)
recipe_num_only <- recipe_pca %>%
step_rm(-all_numeric_predictors())
Here is my XGBoost Model Spec
# XGBoost -----------------------------------------------------------------
model_spec_boost <- boost_tree(
mode = "regression"
# , mtry = 25
# , trees = 25
# , min_n = 10
# , tree_depth = 2
# , learn_rate = 0.3
# , loss_reduction = 0.01
) %>%
set_engine("xgboost")
# * * Testing ----
set.seed(123)
workflow() %>%
add_model(model_spec_boost) %>%
add_recipe(recipe_num_only) %>%
fit(training(splits))
# * * End Test ----
The error I get is the following:
> workflow() %>%
+ add_model(model_spec_boost) %>%
+ add_recipe(recipe_num_only) %>%
+ fit(training(splits))
Error in setinfo.xgb.DMatrix(dmat, names(p), p[[1]]) :
The length of labels must equal to the number of rows in the input data
Timing stopped at: 0 0 0
Everything works until I get to the fit(training(splits))
> workflow() %>%
+ add_model(model_spec_boost) %>%
+ add_recipe(recipe_num_only)
== Workflow ==========================================================================================
Preprocessor: Recipe
Model: boost_tree()
-- Preprocessor --------------------------------------------------------------------------------------
9 Recipe Steps
* step_timeseries_signature()
* step_rm()
* step_dummy()
* step_normalize()
* step_fourier()
* step_normalize()
* step_nzv()
* step_pca()
* step_rm()
-- Model ---------------------------------------------------------------------------------------------
Boosted Tree Model Specification (regression)
Computational engine: xgboost
At a bit of a loss here
