Applied Unsupervised Learning with Python

Appendix

About

This section is included to assist the students to perform the activities present in the book. It includes detailed steps that are to be performed by the students to complete and achieve the objectives of the book.

Chapter 1: Introduction to Clustering

Activity 1: Implementing k-means Clustering

Solution:

1. Load the Iris data file using pandas, a package that makes data wrangling much easier through the use of DataFrames:

   import pandas as pd

   import numpy as np

   import matplotlib.pyplot as plt

   from sklearn.metrics import silhouette_score

   from scipy.spatial.distance import cdist

   iris = pd.read_csv('iris_data.csv', header=None)

   iris.columns = ['SepalLengthCm', 'SepalWidthCm', 'PetalLengthCm', 'PetalWidthCm', 'species']

2. Separate out ...