Python Machine Learning Cookbook - Second Edition

How to do it...

Let's see how to automatically estimate the number of clusters using the DBSCAN algorithm:

1. The full code for this recipe is given in the estimate_clusters.py file that has already been provided to you. Now let's look at how it's built. Create a new Python file, and import the necessary packages:

from itertools import cycle 
import numpy as np 
from sklearn.cluster import DBSCAN 
from sklearn import metrics 
import matplotlib.pyplot as plt 

2. Load the input data from the data_perf.txt file. This is the same file that we used in the previous recipe, which will help us to compare the methods on the same dataset:

# Load datainput_file = ('data_perf.txt')x = []with open(input_file, 'r') as f:    for line in f.readlines(): data = [float(i) ...