R Programming Language Certification Machine Learning with R 2

Question 1

Which R package is used to implement random forest models outside of the tidymodels ecosystem?

Accepted Answer

randomForest

Answer

The randomForest package by Breiman and Cutler directly implements the random forest algorithm and provides functions like randomForest() and importance() for training and interpreting models.

Question 2

In R, which package and function are most commonly used to fit Support Vector Machine (SVM) models?

Accepted Answer

e1071::svm()

Answer

The e1071 package provides the svm() function, which wraps LIBSVM and supports both classification and regression SVMs with multiple kernel options.

Question 3

Which R package is the most widely used for gradient boosting, particularly for tabular data competitions?

Accepted Answer

xgboost

Answer

xgboost (eXtreme Gradient Boosting) is highly optimized for speed and performance, supports regularization, and has been the dominant package for gradient boosting in R competitions and production.

Question 4

What does the 'tuneGrid' parameter control when passed to caret's train() function?

Accepted Answer

The grid of hyperparameter values to search over

Answer

tuneGrid accepts a data frame where each column is a tunable hyperparameter and each row is one combination to evaluate, enabling grid search over the specified hyperparameter space.

Question 5

Which R function from the nnet package fits a single-hidden-layer neural network?

Accepted Answer

nnet()

Answer

nnet() from the nnet package fits a feed-forward neural network with one hidden layer using backpropagation, making it the base R option for simple neural network models.

R Programming Language Certification Practice Test

R Programming Language Certification Practice Test

R Programming Language Certification Machine Learning with R 2