An Effective Unsupervised Machine Learning Technique and Research Challenges

Vishal S. Thakare, Jayshri S. Sonawane

Abstract: Clustering is to categorize data items with similar structures or patterns into the same group for reducing data complexity and facilitating interpretation. It is common technique for statistical data, machine learning and computer science analysis. Clustering is a kind of unsupervised learning. In this paper the various clustering techniques are discussed. Clustering techniques grouping the content of a website or product, segmenting customers or users, creating image segments to be used in image analysis application. Clustering is the technique segment the data to assign each training set. Clustering is the classification of objects into different group, or more precisely, the partitioning of a data set into subsets (cluster), so that the data in each subset(ideally) share some common trait- often according to some defined distance measure.

Keywords: Cluster, K-means, Mean-Shift Clustering, Euclidean Distance, Tanimoto Distance, Agglomerative Hierarchical Clustering

How to Cite?: Vishal S. Thakare, Jayshri S. Sonawane, "An Effective Unsupervised Machine Learning Technique and Research Challenges", Volume 12 Issue 5, May 2023, International Journal of Science and Research (IJSR), Pages: 2141-2143, https://www.ijsr.net/getabstract.php?paperid=SR23523214829, DOI: https://dx.doi.org/10.21275/SR23523214829