MCQ IN COMPUTER SCIENCE & ENGINEERING

Detailed explanation-1: -A machine learning problem involves four attributes plus a class. The attributes have 3, 2, 2, and 2 possible values each.

Detailed explanation-2: -There are four basic approaches:supervised learning, unsupervised learning, semi-supervised learning and reinforcement learning. The type of algorithm data scientists choose to use depends on what type of data they want to predict.

Detailed explanation-3: -Within machine learning, there are many kinds of algorithms. These can be divided into three main categories: supervised learning, unsupervised learning and reinforcement learning.

Detailed explanation-4: -Attributes are the items of data that are used in machine learning. Attributes are also referred as variables, fields, or predictors. In predictive models, attributes are the predictors that affect a given outcome.