md_regression

##Description The Multidimensional Regression class acts as a meta-algorithm for regression that allows several one-dimensional regression algorithms (such as Linear Regression), to be combined together to allow an M-dimensional signal to be mapped to an N-dimensional signal. This works by training N separate regression algorithms (one for each dimension), each with an M-dimensional input.

Multidimensional Regression: Multidimensional Regression is a meta-algorithm that allows several one-dimensional regression algorithms (such as Linear Regression), to be combined together to allow an M-dimensional input signal to be mapped to an N-dimensional signal. This works by training N separate regression algorithms (one for each dimension), each with an M-dimensional input. In this example, a 3-dimensional signal is mapped to a 2-dimensional output signal using the Multidimensional Regression meta-algorithm.

In addition to enabling one-dimensional regression algorithms (such as Linear Regression) to be used for mapping N-dimensional output signals, Multidimensional Regression can also be useful for multi-dimensional regression algorithms (such as Multi Layer Perceptron), as it enables you to train N separate MLP algorithms (one for each output signal), which might provide better mapping results than trying to train one MLP algorithm that can successfully map all N-dimensions at once.

The Multidimensional Regression algorithm is a supervised learning algorithm that can be used for regression for any type of M-dimensional signal.

The Multidimensional Regression algorithm is part of the GRT regression modules.

##Advantages The Multidimensional Regression algorithm is a meta-algorithm for regression that can map an M-dimensional signal to a N-dimensional signal. You can use any of the GRT regression algorithms with Multidimensional Regression.

##Disadvantages The main limitation of the Multidimensional Regression algorithm is that, if you are mapping an M-dimensinal signal to an N-dimensional signal, then the Multidimensional Regression algorithm needs to train N independent regression algorithms.

##Things To Know You should always enable scaling with Multidimensional Regression, as this will give you much better results.

##Training Data Format You should use the RegressionData data structure to train the Multidimensional Regression algorithm.

##Example Code Multidimensional Regression