For a film series that is just as mind-bending now as it was when it first came out, "The Matrix" movies are relatively easy ...

The example shows the benefits of linear regression; that is, you are using a single line that you draw through the plot points. The line might go up or down, ...

Learn how to detect outliers, how they impact your regression coefficients, and how to trim or winsorize them. Compare the pros and cons of each method.

Sparse matrix regression (SMR) is a two-dimensional supervised feature selection method that can directly select the features on matrix data. It uses several couples of left and right regression ...

This manuscript provides valuable information on the neurodynamics of emotional processing while participants were watching movie clips. The methods and results were solid in deciphering the ...

Low-rank matrix regression is a fundamental problem in data science with various applications in systems and control. Nuclear norm regularization has been widely applied to solve this problem due to ...

The diagram in Figure 2 gives you a rough idea of support vector regression for a scenario where there is just one predictor variable x. Each dot is a training data item. The red line is the linear ...