What algorithms can perform multiple output regression?

There are many regression algorithms that can obtain a dependent variable through multiple independent variables. For example, support vector machine regression algorithm can be used to calculate and fit the reflectance of 128 spectral bands to obtain an index, namely 128 x and 1 y.

I found some algorithms, they are often used for image recognition, I can't use these algorithms.

Is there an algorithm that can get multiple dependent variables from multiple independent variables? Let's say I use 128 x's to fit between 2 and 15 y's.

[John D'Errico]

A regression algorithm depends on the model used. A simple regression that is linear in the parameters requires nothing more than backslash to perform. Other "regressions" will as I said, depend on the model you will specify. And until you say what that is, it is impossible to say more.

Answer 1

[the cyclist]

The mvregress function in the Statistics and Machine Learning Toolbox will perform linear regressions with multiple dependent variables.

Take a look at my answer here for an example with some common design matrices. There are of course examples in the documentation page I linked, as well.