Maybe you could find the answer from the following website:

https://www.mathworks.com/help/stats/support-vector-machine-regression.html

Hi,

You can consider each of the input in one column.

In new version of Matlab, SVR would be available in toolbox.

Thanks,

What do you mean by SVR? is it Support Vector Machine Regression? If yes.

Since you want to process 5 inputs at the same time then it's multidimensional forecasting. therefore, it's not coefficients to forecast the five dimensions at the same time using SVM because all the cross-information between the input-data will not be processed which leads to efficient forecasting. Usually we use complex SVM for two dimensional forecasting and quaternion SVM for three or four dimensional forecasting. For up to eight inputs they use octonions but the SVM is not extended to octonions yet.

Why you want to process the five inputs at the same time? If your lecturer/ supervisor told you to do that you can simply use five SVR models each one to process one input and they will share the same output and error and produce one output. But tell your supervisor/lecturer that this way will not process the second order statistics available between the input data.