Classification

Abstract

In the world of data mining, classification reigns supreme as a popular technique for supervised learning. Its ability to identify patterns in data by dividing it into training sets and utilizing machine learning makes it an essential tool in answering critical questions related to data. For instance, classification can aid businesses in identifying customers with high purchasing potential. One of the standout features of classification is k-nearest neighbors (k-NN), which allows data to be classified according to the training data set. Decision trees are also commonly used to support decision making by producing easily interpretable diagrams. RapidMiner is an outstanding data mining tool that can employ a range of classification techniques, including k-NN, decision trees, and naïve Bayes. In this book, readers can follow a step-by-step guide to using these techniques with RapidMiner to achieve effective data classification.