Can we use linear regression to solve classification problems?

There are two things that explain why Linear Regression is not suitable for classification. The first one is that Linear Regression deals with continuous values whereas classification problems mandate discrete values. The second problem is regarding the shift in threshold value when new data points are added.

Which of the following is the reason why linear regression is not suitable for modeling binary responses?

With binary data the variance is a function of the mean, and in particular is not constant as the mean changes. This violates one of the standard linear regression assumptions that the variance of the residual errors is constant.

Which regression is used for solving classification problem?

The basis of logistic regression is the logistic function, also called the sigmoid function, which takes in any real valued number and maps it to a value between 0 and 1. Logistic regression model takes a linear equation as input and use logistic function and log odds to perform a binary classification task.

Can you use regression for classification?

Logistic regression predicts probabilities, and is therefore a regression algorithm. However, it is commonly described as a classification method in the machine learning literature, because it can be (and is often) used to make classifiers.

Which regression is used for solving the classification problem?

How do you solve non-linear regression?

Take the following nonlinear regression equations: The Michaelis-Menten model: f(x,β) = (β1 x) / (β 2 + x). Y = β0 + (0.4 – β0)e-β1(xi-5) + εi….Y = f(X,β) + ε

1. X = a vector of p predictors,
2. β = a vector of k parameters,
3. f(-) = a known regression function,
4. ε = an error term.

When can linear regression not be used?

First, never use linear regression if the trend in the data set appears to be curved; no matter how hard you try, a linear model will not fit a curved data set. Second, linear regression is only capable of handling a single dependent variable and a single independent variable.

Can we use regression for classification?

Why do we prefer logistic regression over linear regression in the classification problems?

Linear Regression is used to handle regression problems whereas Logistic regression is used to handle the classification problems. Linear regression provides a continuous output but Logistic regression provides discreet output.