1. Customer Segmentation Using UMAP and HDBSCAN
- Author
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Chandrasekaran K S, Jeevanantham T, Jemima Blessy R, and Jesila foumiya Z
- Subjects
Machine Learning ,Customer Segmentation ,Correlation of Variables ,UMAP ,Preprocessing ,Clustering ,HDBSCAN ,Visualization - Abstract
Customer segmentation is now a very common strategy for keeping customers happy and generating revenue for businesses. Customers from various organisations are categorised in this project based on behavioural traits including their ability to spend money and their income. In order to categorise the customers and create clusters, a computer algorithm known as UMAP and HDBSCAN is used. With the aid of these clusters, the business is better able to target specific clients and promote to them via advertising campaigns and social media platforms about content in which they have a genuine interest.Unsupervised machine learning techniques, such UMAP and HDBSCAN, have grown in popularity in recent years for client segmentation.Using UMAP, high-dimensional data can be reduced to low-dimensional space while retaining its structure and relationships.HDBSCAN is a density-based clustering technique that finds clusters of varied sizes and forms, and assigns each data point to a cluster or a noise category. Because they allow for quick and precise customer grouping, UMAP and HDBSCAN offer a potent combination for customer segmentation.
- Published
- 2023
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