MCQ IN COMPUTER SCIENCE & ENGINEERING

Detailed explanation-1: -A supervised machine learning model will learn to identify patterns and relationships within a labelled training dataset. Once the relationship between input data and expected output data is understood, new and unseen data can be processed by the model.

Detailed explanation-2: -What is unsupervised learning? Unsupervised learning, also known as unsupervised machine learning, uses machine learning algorithms to analyze and cluster unlabeled datasets. These algorithms discover hidden patterns or data groupings without the need for human intervention.

Detailed explanation-3: -We can think of unsupervised learning problems as being divided into two categories: clustering and association rules. Clustering is an unsupervised learning technique, which groups unlabeled data points based on their similarity and differences.

Detailed explanation-4: -Unsupervised Learning. Unsupervised learning is very much the opposite of supervised learning. It features no labels. Instead, our algorithm would be fed a lot of data and given the tools to understand the properties of the data.