Which algorithm is used to predict a numeric value from input features?

Which algorithm is used to predict a numeric value from input features?

• A. Linear regression
• B. Logistic regression
• C. Support vector machine
• D. Decision tree

Answer: (A)

Predicting a numeric value from input features is a regression task. Linear regression directly models a linear relationship between the features and the continuous output, estimating coefficients that minimize prediction error so the model can forecast a numeric value for new inputs. This makes it the best match for the goal of numeric prediction, since the other options are geared toward different outcomes: logistic regression predicts categories (classification), while support vector machines can perform either classification or regression (but are more advanced and not the most direct example), and decision trees can produce numeric predictions as well but are not the simplest or most textbook method for this purpose.

Predicting a numeric value from input features is a regression task. Linear regression directly models a linear relationship between the features and the continuous output, estimating coefficients that minimize prediction error so the model can forecast a numeric value for new inputs. This makes it the best match for the goal of numeric prediction, since the other options are geared toward different outcomes: logistic regression predicts categories (classification), while support vector machines can perform either classification or regression (but are more advanced and not the most direct example), and decision trees can produce numeric predictions as well but are not the simplest or most textbook method for this purpose.