Over the last couple of articles, We learned different classification and regression algorithms.
Now in this article, We are going to learn entirely another type of algorithm. Which falls into the unsupervised learning algorithms.
If you were not aware of unsupervised learning algorithms, all the machine learning algorithms mainly classified into two main categories.
- Supervised learning algorithms
- Unsupervised learning algorithms
All the classification and regression algorithms belong to supervised learning algorithms. The other set of algorithms which fall under unsupervised learning algorithms are clustering algorithms.
In fact, the foremost algorithms to study in unsupervised learning algorithms is clustering analysis algorithms. Today we are going to learn an algorithm to perform the cluster analysis.
We have a decent number of algorithms to perform cluster analysis; In this article, we will be learning how to perform the clustering with the Hierarchical clustering algorithm.
Before we drive further. Let’s have a look at the table of contents.
Table of contents:
- What is clustering analysis?
- Clustering analysis example
- Hierarchical clustering
- Agglomerative clustering
- Divisive clustering
- Clustering linkage comparison
- Implementing hierarchical clustering in R programming language
- Data preparation
- Packages need to perform hierarchical clustering
- Visualizing clustering in 3d view
- Complete code