Project using the kNN (k-Nearest Neighbors) algorithm to solve a classification problem.
The kNN is a simple and robust classifier, which is used in different applications.
I will use the Iris dataset. The dataset was first introduced by statistician R. Fisher and consists of 50 observations from each of three species Iris (Iris setosa, Iris virginica and Iris versicolor). For each sample, 4 features are given: the sepal length and width, and the petal length and width.
The goal is to train kNN algorithm to distinguish the species from one another.
The dataset can be downloaded from UCI Machine Learning Repository: https://archive.ics.uci.edu/ml/machine-learning-databases/iris/.