Tag Archives: Random Forests

Bagging

Ensemble methods combine multiple classifiers into a single output. Some ensemble methods may combine different types of classifiers, but the ones we will focus on here combine multiple iterations of the same type of classifier. These methods belong to a family of ensemble methods called “Perturb and Combine”. Perturb and Combine Some methods of classification […]

Random Forests (R)

We will apply the random forest method to the Adult dataset here. We will begin by importing the data, doing some pre-filtering and combining into classes, and generating two subsets of the data: The training set, which we will be using to train the random Forest model, and the evaluation set, which we will use […]