Random Forest

Random forest models are a popular machine learning algorithm in data science. Random forests can be used for both regression and classification tasks and are known for high accuracy and their ability to handle large datasets. In this lesson, we delve into the steps involved in creating a random forest model using tidymodels.

At a very high level, a random forest model uses many decision trees to make predictions. Each decision tree is built using a different subset of the training data, and the final prediction is made by taking the average or majority vote of the predictions from all the trees.