R Programming Language Certification Machine Learning with R

Question 1

Which R package provides a unified interface to train and evaluate many machine learning models?

Accepted Answer

caret

Answer

lattice

Answer

forecast

Answer

stringr

Question 2

In the caret package, which function is used to train a machine learning model?

Accepted Answer

train()

Answer

fit()

Answer

model()

Answer

learn()

Question 3

Which tidymodels package is responsible for model specification (defining the model type and engine)?

Accepted Answer

parsnip

Answer

recipes

Answer

rsample

Answer

yardstick

Question 4

What is the primary purpose of k-fold cross-validation in machine learning?

Accepted Answer

To obtain a more reliable estimate of model performance

Answer

To increase training data size

Answer

To speed up model training

Answer

To reduce the number of features

Question 5

In R's tidymodels framework, which package handles data preprocessing and feature engineering steps?

Accepted Answer

recipes

Answer

parsnip

Answer

yardstick

Answer

workflows

Question 6

Which function from the rsample package creates a stratified train/test split in R?

Accepted Answer

initial_split()

Answer

train_test_split()

Answer

split_data()

Answer

partition()

Question 7

Which R metric from the yardstick package is most appropriate for evaluating a binary classification model on imbalanced data?

Accepted Answer

roc_auc()

Answer

accuracy()

Answer

rmse()

Answer

rsq()