What is unsupervised learning?

Abstract

Unsupervised learning is a machine learning approach used to find patterns and structures in unlabeled data, without relying on predefined categories or labels. It is commonly used for exploratory data analysis, clustering, association rule mining, and dimensionality reduction. This article discusses various unsupervised learning techniques, including clustering algorithms such as k-means clustering and hierarchical clustering, association rules such as Apriori algorithm, and dimensionality reduction methods like principal component analysis and singular value decomposition. The article also highlights potential challenges of unsupervised learning, such as computational complexity, longer training times, higher risk of inaccurate results, and the need for human intervention to validate output variables. – AI-generated abstract.