What type of function attempts to predict the value of a continuous target using one or more independent inputs?

The type of function that aims to predict the value of a continuous target using one or more independent inputs is a linear function. In the context of regression analysis, which is often employed for predicting continuous outcomes, linear functions establish a relationship between dependent and independent variables by fitting a straight line to the data. This line represents the best estimate of the target variable based on the input features.

Linear regression assumes that there is a linear relationship between the inputs (predictors) and the output (target variable), making it a fundamental technique in predictive modeling. When the relationship is modeled appropriately, linear regression can effectively capture trends and patterns in the data, allowing for effective predictions of continuous outcomes.

While other types of functions, such as polynomial, logistic, and exponential, can also be used for modeling, they are suited for different scenarios. For example, polynomial functions can model non-linear relationships, logistic functions are used for binary classification, and exponential functions can model growth processes, such as population growth, which are not typically focused on continuous target variable prediction in the same manner as linear functions.