I am wondering how I can perform multivariate multiple regression (multiple outcomes with multiple features) utilizing the tidymodels framework. Is it possible?
I had to do some digging to find that tidymodels does not appear to currently support multivariate multiple regression:
I watched and followed along with many of the outstanding Tidy Tuesday examples taught by @julia to learn Tidymodels. I believe what I'm trying to do is going to be most similar to the following example that I've modified from tidymodels.org (XGBoost Regression ) .
'Ridership' from the Chicago dataset was predicted from 2 columns. What if instead I want to predict Ridership and Cubs_Home , and from all columns ? Is this possible?
library(tidymodels)
tidymodels_prefer()
data(Chicago)
n <- nrow(Chicago)
#split into training and testing sets
Chicago_train <- Chicago[1:(n - 7), ]
Chicago_test <- Chicago[(n - 6):n, ]
#model specs
bt_reg_spec <-
boost_tree(trees = 15) %>%
# This model cā¦
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system
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March 20, 2024, 7:05pm
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