I have managed to build a decision tree model using the tidymodels package but I am unsure how to pull the results and plot the tree. I know I can use the rpart and rpart.plot packages to achieve t...

I have a large dataset that looks like this. I was wondering if there is a clever way to apply a t-test, in each row, aka gene, and compare the counts between humans and mice. I want to compete in ...

I have the following script using tidymodels' agua package: library(tidymodels) library(agua) library(ggplot2) theme_set(theme_bw()) h2o_start() data(concrete) set.seed(4595) concrete_split <- ...

I have the following codes for creating a tidymodels workflow with lightgbm model. However, there is some problem when I tried to save into a .rds object and predict library(AmesHousing) library(tr...

I'm trying to adopt tidymodels into my processes, but I'm running into a challenge with saving workflows. The file size for workflow objects is many times larger than the data used to build the mod...

Is there any R package to obtain a pairwise distance list if my input file is a distance matrix For eg, if my input is a data.frame like this: A1 B1 C1 D1 A1 0 0.85 0.45 0.96 B1 0 0.85 0.56 C...

I am trying to build a catboost model within the tidymodels framework. Minimal reproducible example is given below. I am able to use the DALEX and modelStudio packages to get model explanations but...

This question refers to Obtaining summary shap plot for catboost model with tidymodels in R. Given the comment below the question, the OP found a solution but did not share it with the community so...

I want to evaluate the performance of several (mostly) linear regression models on the same dataset. I thought maybe using tidymodels packages along with the workflowsets::workflow_set() might work...

I try to use tidymodels to tune the workflow with recipe and model parameters. When tuning a single workflow there is no problem. But when tuning a workflowsets with several workflows it always fai...

I am using tidymodels to create a Random Forrest prediction. I have test data that contains a new factor level not present in the training data which results in the error: 1: Novel levels found in ...

The code below works correctly and has no errors that I know of, but I want to add more to it. The two things I want to add are: 1 - Predictions of the model on the training data to the final plot....

I have a binary classification problem and used a random forest and a logistic regression. From the results of conf_mat, the collect_metrics() and collect_predictions I want to change my models to ...

I want to perform penalty selection for the LASSO algorithm and predict outcomes using tidymodels. I will use the Boston housing dataset to illustrate the problem. library(tidymodels) library(tidyv...

I've recently been using tidymodels to run models and select parameters that best satisfy some objective function. For example using a hypothetical regression on mtcars data (using the regression e...

After designing a Tidymodels recipe-based workflow, which is tuned then fitted to some training data, I'm not clear what objects (fitted "workflow", "recipe", ..etc) should be s...

I always finish up my model to fit and predict without using prep(), bake(), or juice(): rec_wflow <- workflow() %>% add_model(lr_mod) %>% add_recipe(rec) data_fit <- rec_wflow...

The answer to this question clearly explains how to retrieve tidy regression results by group when running a regression through a dplyr pipe, but the solution is no longer reproducible. How can one...

I estimated a glmnet logistic regression using tidymodels. But I couldn't figure out 2 things, which are closely related, in tidymodels: a) how to extract the estimated coefficients b) save the es...

I've put together a data preprocessing recipe for the recent coffee dataset featured on TidyTuesday. My intention is to generate a workflow, and then from there tune a hyperparameter. I'm specifica...

I read the introduction to tidymodels and I am confused about what prep(), bake() and juice() from the recipes package do to the data. What each does? I honestly found confusing to have such names ...

The dataset can be found here: https://www.kaggle.com/mlg-ulb/creditcardfraud I am trying to use tidymodels to run ranger with 5 fold cross validation on this dataset. I have have 2 code blocks....