Datasets

Data is undoubtedly the most important component of machine learning. If there was no data, we wouldn't have a common purpose. In most cases, the purpose for which the data is collected defines the problem itself. As we know that the variable might be of several types, the way it is stored and organized is also very important.

Lee and Elder (1997) considered a series of datasets and introduced the need for ensemble models. We will begin by looking at the details of the datasets considered in their paper, and we will then refer to other important datasets later on in the book.