Abstract
Unsupervised learning is a complex processing task involving the
identification of patterns in datasets having data points that are neither labeled nor
classified. Unsupervised learning is a kind of machine learning algorithm that can be
used to draw useful conclusions without the presence of labeled responses in the input
data. In the following chapter, we will discuss Clustering (K-means Clustering,
Hierarchical Clustering), and Principal Component Analysis.
Keywords: Clustering, Principal component analysis, Unsupervised learning.
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