How to do Agglomerative Clustering in Python

Agglomerative Clustering is a method of clustering that starts with each data point as its own cluster, and then merges the closest clusters together until only the desired number of clusters remains. This method is known as a “bottom-up” approach because it starts with the smallest units and merges them together. In this article, we will go over the basics of how to do Agglomerative Clustering in Python.

First, we need to import the necessary libraries such as Numpy and Pandas, which will help us handle our data. Next, we will import the AgglomerativeClustering class from the sklearn.cluster library, which will be used to create our clusters.

Once we have our libraries and classes imported, we can start creating our clusters. To do this, we will first need to load our data into a Pandas dataframe. We can do this by using the read_csv function, which will allow us to read in data from a CSV file.

Once our data is loaded, we can create our model by instantiating the AgglomerativeClustering class. We need to set the number of clusters we want in the model and the linkage criteria(ward, complete or average) which is the method used to calculate the distance between clusters.

Once the model is instantiated, we can fit the model to our data using the fit_predict method. This will cluster our data into the specified number of clusters.

To check the accuracy of our model, we can use different metrics such as silhouette score and calinski harabasz index. The higher the silhouette score and calinski harabasz index, the better our model is at clustering the data.

In conclusion, doing Agglomerative Clustering in Python is a straightforward process. By using the sklearn.cluster library, we can easily load and cluster our data using the AgglomerativeClustering class. By tuning the number of clusters, linkage criteria and using metrics, we can optimise the accuracy of our model and make more accurate clusters.

In this Learn through Codes example, you will learn: How to do Agglomerative Clustering in Python.