Implementing k-means from scratch

We use the iris dataset from scikit-learn as an example. Let's first load the data and visualize it. We herein only use two features out of the original four for simplicity:

>>> from sklearn import datasets>>> iris = datasets.load_iris()>>> X =[:, 2:4]>>> y =

Since the dataset contains three iris classes, we plot it in three different colors, as follows:

>>> import numpy as np>>> from matplotlib import pyplot as plt>>> y_0 = np.where(y==0)>>> plt.scatter(X[y_0, 0], X[y_0, 1])>>> y_1 = np.where(y==1)>>> plt.scatter(X[y_1, 0], X[y_1, 1])>>> y_2 = np.where(y==2)>>> plt.scatter(X[y_2, 0], X[y_2, 1])>>>

This will give you the following output for the origin data plot:

Assuming ...

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