MCQ IN COMPUTER SCIENCE & ENGINEERING

Detailed explanation-1: -Clustering is the most common unsupervised learning algorithm used to explore the data analysis to find hidden patterns or groupings in the data (Fig. 12.3).

Detailed explanation-2: -Unsupervised learning uses machine learning algorithms to analyze and cluster unlabeled data sets. These algorithms discover hidden patterns in data without the need for human intervention (hence, they are “unsupervised”).

Detailed explanation-3: -In Data mining, the problem of unsupervised learning is that of trying to find hidden structure in unlabeled data.

Detailed explanation-4: -Unsupervised learning is a technique of machine learning where hidden patterns are uncovered from unlabelled datasets.

Detailed explanation-5: -Clustering is an unsupervised learning technique, which groups unlabeled data points based on their similarity and differences. Hence, points are grouped into clusters in such a way that those in a same group have the most similarity with each other, while points in different groups have little to no similarities.