A quasi-Bayes linear regression (QBLR) algorithm is developed to execute the sequential adaptation where the regression matrix is estimated using QB theory. In the estimation, we specify the prior ...

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 ...

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 ...