Ridge regression

In layman’s terms, Ridge regression adds one more term to linear regression’s cost function to reduce error. Ridge regression is a model-tuning method used to analyze data that suffer from multicollinearity. This method performs L2 regularization. When the issue of multicollinearity occurs, least-squares are unbiased, and variances are large; this results in predicted values being … Read more

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Polynomial regression

“Polynomial Regression is a form of linear regression in which the relationship between the independent variable x and dependent variable y is modeled as an nth-degree polynomial. Polynomial regression fits a nonlinear relationship between the value of x and the corresponding conditional mean of y.” As stated in formal terms, this definition of polynomial regression … Read more

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Logistic Regression

Logistic regression is one of the most popular algorithms for classification problems. It is called regression even though it is not a regression algorithm because the underlying technology is similar to Linear Regression. The term “logistic” comes from the statistical model used (logit model). As seen in earlier releases, classification algorithms are used to classify … Read more

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