[TBD]Role of Hierarchical clustering in current data science

Introduction

Hierarchical clustering is an unsupervised machine learning algorithm, which is used to group the unlabeled datasets into a cluster and also known as hierarchical cluster analysis or HCA. If you are interested to understand its role in current data science, then this document helps.

Laymen explanation

Technical explanation

The goal of hierarchical cluster analysis is to build a tree diagram where the cards that were viewed as most similar by the participants in the study are placed on branches that are close together. Cards that join together sooner are more similar to each other than those that join together later.

There are two types of tree making approaches

• Bottom up approach (Agglomerative)

• Top down approach (Divisive)

Cutting the tree at a given height will give a partitioning clustering at a selected precision. In this example, cutting after the second row (from the top) of the dendrogram will yield clusters {a} {b c} {d e} {f}. Cutting after the third row will yield clusters {a} {b c} {d e f}, which is a coarser clustering, with a smaller number but larger clusters.

Advantages

• No apriori information about the number of clusters required.

• Easy to implement

  • It can be used for non-convex clustering

Challenges

• The algorithm can never undo any previous steps. So for example, the algorithm clusters 2 points, and later on we see that the connection was not a good one, the program cannot undo that step.

• The time complexity for the clustering can result in very long computation times, in comparison with efficient algorithms, such k-Means.

• If we have a large dataset, it can become difficult to determine the correct number of clusters by the dendrogram.

Role in machine learning

Social Network Analysis

Relevance with neural networks

This paper tells that Self Organizing Map (SOM) neural network clustering methodology and demonstrate that it is superior to the hierarchical clustering methods.

Reference

https://www.youtube.com/watch?v=0jPGHniVVNc

https://youtu.be/pBAbMbgaBAk?t=1535

https://sites.google.com/site/dataclusteringalgorithms/hierarchical-clustering-algorithm

https://www.sciencedirect.com/topics/computer-science/hierarchical-cluster-analysis

https://en.wikipedia.org/wiki/Hierarchical_clustering

https://www.displayr.com/strengths-weaknesses-hierarchical-clustering/

https://www.quora.com/What-are-the-drawbacks-of-Hierarchical-Clustering

https://www.simplilearn.com/tutorials/data-science-tutorial/hierarchical-clustering-in-r

https://stats.stackexchange.com/questions/432412/can-agglomerative-clustering-hierarchical-form-non-convex-clusters

https://www.javatpoint.com/hierarchical-clustering-in-machine-learning