Coding the k-means algorithm

Let's look at how we can code the k-means algorithm in Python:

1. First, let's import the packages that we will need to code for the k-means algorithm. Note that we are importing the sklearn package for k-means clustering:

from sklearn import cluster
import pandas as pd
import numpy as np

1. To use k-means clustering, let's create 20 data points in a two-dimensional problem space that we will be using for k-means clustering:

dataset = pd.DataFrame({
    'x': [11, 21, 28, 17, 29, 33, 24, 45, 45, 52, 51, 52, 55, 53, 55, 61, 62, 70, 72, 10],
    'y': [39, 36, 30, 52, 53, 46, 55, 59, 63, 70, 66, 63, 58, 23, 14, 8, 18, 7, 24, 10]
})

1. Let's have two clusters (k = 2) and then create the cluster by calling the fit functions:

myKmeans = cluster.KMeans(n_clusters=2)
myKmeans.fit(dataset)

1. Let's create a variable named centroid that is an array that holds the location of the center...