I managed to create a dataset with 6 clusters and visualize it with the code below, now I would like to visualize demonstration of update of the cluster centroids in KMeans algorithm. This demonstration should include first four iterations by generating 2×2-axis figure
Here is my code:
# import statements from sklearn.datasets import make_blobs import numpy as np import matplotlib.pyplot as plt # create blobs data = make_blobs(n_samples=200, n_features=6, centers=6, cluster_std=1.6, random_state=50) # create np array for data points points = data # create scatter plot plt.scatter(data[:,0], data[:,1], c=data, cmap='jet',marker="+",label="Original Data") plt.xlim(-15,15) plt.ylim(-15,15) plt.show()
How can I implement this algorithm? It has been asked before using R but, I would like to do it in python. Can you help me visualize the first 4 iterations?
Output should be like: