The Unsupervised Learning Workshop

Appendix

1. Introduction to Clustering

Activity 1.01: Implementing k-means Clustering

Solution:

1. Import the required libraries:

   from sklearn.datasets import make_blobs

   from sklearn.cluster import KMeans

   from sklearn.metrics import accuracy_score, silhouette_score

   import matplotlib.pyplot as plt

   import pandas as pd

   import numpy as np

   from scipy.spatial.distance import cdist

   import math

   np.random.seed(0)

   %matplotlib inline

2. Load the seeds data file using pandas:

   seeds = pd.read_csv('Seed_Data.csv')

3. Return the first five rows of the dataset, as follows:

   seeds.head()

   The output is as follows:

   

   Figure 1.25: Displaying the first five rows of the dataset

4. Separate ...