MCQ IN COMPUTER SCIENCE & ENGINEERING

Detailed explanation-1: -In Classification, the output variable must be a discrete value. The task of the regression algorithm is to map the input value (x) with the continuous output variable(y).

Detailed explanation-2: -The output variable has to be a discrete value. The regression algorithm’s task is mapping input value (x) with continuous output variable (y). The classification algorithm’s task mapping the input value of x with the discrete output variable of y. They are used with continuous data.

Detailed explanation-3: -It is used to assess a classifier’s performance, and the output is a probability value between 1 and 0. A successful binary classification model should have a log loss value that is close to 0.

Detailed explanation-4: -Categorical data is a type of data that is used to group information with similar characteristics, while numerical data is a type of data that expresses information in the form of numbers. Why do we need encoding? Categorical variables can be divided into two categories: Nominal: no particular order.

Detailed explanation-5: -Unlike regression, the output variable of Classification is a category, not a value, such as “Green or Blue", “fruit or animal", etc. Since the Classification algorithm is a Supervised learning technique, hence it takes labeled input data, which means it contains input with the corresponding output.