What is logistic regression? Logistic regression is used in classification problems. Let’s say we are given the sepal length, sepal width, petal length, and petal width of two types of flowers. Based on these parameters, we have to classify the type of flower. Here,...

What is the ElasticNet regression? In our previous articles, we discussed Ridge regression and Lasso regression. Lasso regression gives a good performance, but it has some disadvantages. They are: If the number of variables is more than the number of observations,...

What is the Lasso regression? In our previous article, we discussed the Ridge regression. Using the Ridge regression, we penalize less important predictor variables so that the variables are kept, but their effects are less. In linear regression, we calculate the...

What is Ridge regression? If there are too many predictor variables or features, then that may cause various problems. So, we can find important variables and keep them and omit the unimportant ones. But, in a practical scenario, it may not be the case where a...

In one of our previous articles, we discussed polynomial regression using the sklearn Python library. We read the “mpg” dataset from the seaborn library and created a polynomial regression model that takes the horsepower of a car as input and determines its mpg or...