Machine Learning Algorithms - Second Edition

Dendrograms

To better understand the agglomeration process, it's useful to introduce a graphical method called a dendrogram, which shows in a static way how the aggregations are performed, starting from the bottom (where all samples are separated) to the top (where the linkage is complete). Unfortunately, scikit-learn doesn't support it. However, SciPy provides some useful built-in functions.

Let's start by creating a dummy dataset:

from sklearn.datasets import make_blobsnb_samples = 25X, Y = make_blobs(n_samples=nb_samples, n_features=2, centers=3, cluster_std=1.5)

To avoid excessive complexity in the resulting plot, the number of samples has been kept very low. In the following graph, there's a representation of the dataset:

Simple dataset ...