RapidMiner

Chapter 3

k-Nearest Neighbor Classification I

M. Fareed Akhtar

Fastonish, Australia

3.1 Introduction

This chapter explains the k-NN classification algorithm and its operator in RapidMiner. The Use Case of this chapter applies the k-NN operator on the Teacher Evaluation dataset. The operators explained in this chapter are: Read URL, Rename, Numerical to Binominal, Numerical to Polynominal, Set Role, Split Validation, Apply Model, and Performance.

The k-Nearest Neighbor algorithm is based on learning by analogy, that is, by comparing a given test example with the training examples that are similar to it. The training examples are described by n attributes. Each example represents a point in an n-dimensional space. In this way, all of the training ...