MCQ IN COMPUTER SCIENCE & ENGINEERING

Detailed explanation-1: -Supervised learning, also known as supervised machine learning, is a subcategory of machine learning and artificial intelligence. It is defined by its use of labeled datasets to train algorithms that to classify data or predict outcomes accurately.

Detailed explanation-2: -Unsupervised Learning areas of application include market basket analysis, semantic clustering, recommender systems, etc. The most commonly used Supervised Learning algorithms are decision tree, logistic regression, linear regression, support vector machine.

Detailed explanation-3: -Supervised learning is a machine learning approach that’s defined by its use of labeled datasets. These datasets are designed to train or “supervise” algorithms into classifying data or predicting outcomes accurately.

Detailed explanation-4: -A supervised learning algorithm takes a known set of input data and known responses to the data (output) and trains a model to generate reasonable predictions for the response to new data. Use supervised learning if you have known data for the output you are trying to predict.