MCQ IN COMPUTER SCIENCE & ENGINEERING

Detailed explanation-1: -Binary classification is the task of classifying the elements of a set into two groups (each called class) on the basis of a classification rule.

Detailed explanation-2: -Multiclass Classification is where each data sample is assigned one and only one label from more than two classes. Multi-label Classification is a type of supervised machine learning algorithm that can be used to assign zero or more labels to each data sample.

Detailed explanation-3: -Multi-label classification involves predicting zero or more class labels. Unlike normal classification tasks where class labels are mutually exclusive, multi-label classification requires specialized machine learning algorithms that support predicting multiple mutually non-exclusive classes or “labels.”

Detailed explanation-4: -Binary classification involves splitting items into only two classes. The example above was binary classification, as it split the reviews into “positive” and “negative”. Another example of binary classification is spam filtering, as an email is either classified as “spam” or “not spam”.