Q.No.5. The _________ learning model predicts a continuous target variable as a linear functionof input features.

The answer is "linear regression" learning model predicts a continuous target variable as a linear function of input features.

In linear regression, the relationship between the input variables (features) and the output variable (target) is modeled as a linear equation. It assumes that changes in the input variables will produce proportional changes in the output. Linear regression is commonly used in various fields, including economics, biology, and social sciences, for predicting outcomes based on different predictor variables. The model can be represented mathematically as:

$y = \beta_0 + \beta_1 x_1 + \beta_2 x_2 + \ldots + \beta_n x_n + \epsilon$

where $y$ is the predicted outcome, $x_1, x_2, \ldots, x_n$ are the input features, $\beta_0$ is the y-intercept, $\beta_1, \ldots, \beta_n$ are the coefficients for each feature, and $\epsilon$ is the error term.