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 ...

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 ...

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 ...

Researchers at EPFL have created a mathematical model that helps explain how breaking language into sequences makes modern AI ...

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, ...

This valuable study identifies asymmetric dimethylarginine (ADMA) histones as potential determinants of the initial genomic binding of Rhino, a Drosophila-specific chromatin protein essential for ...

Correlation coefficients are used to measure the strength of the linear relationship between two variables.; A correlation coefficient greater than zero indicates a positive relationship, while a ...

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 ...

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.