In this exercise, we will compare kNN to neural networks where we have a small dataset. We will be using the iris dataset imported from the scikit-learn library.
To begin, we will first discuss the basics of kNN. The kNN classifier is a nonparametric classifier that simply stores the training data, D, and classifies each new instance using a majority vote over its set of k nearest neighbors, computed using any distance function. For a kNN, we need to choose the distance function, d, and the number of neighbors, k:
You can also refer to the code file at the following GitHub link: https://github.com/PacktPublishing/Hands-on-One-Shot-Learning-with-Python/blob/master/Chapter01/CodingExercise01.ipynb ...
