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...
What is Leave One Out Cross Validation, and how does it work? In our previous article, we discussed what k-fold cross-validation is and how to implement it using sklearn in Python. Leave One Out Cross Validation is a specific variation of k-fold cross-validation where...
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...
What is k-fold cross-validation, and how does it work? A k-fold cross-validation is an approach using which one can estimate the performance of a machine learning model. In k-fold cross-validation, the dataset is divided into k parts called k folds. Then, the (k-1)...
What is polynomial regression? In linear regression, we consider a linear relationship between the target and the predictor variables. But sometimes the target variable does not have a linear relationship with the predictor variables or the features. For example,...
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