MATLAB: Correlation of input variables in ANN

correlation annDeep Learning Toolbox

Hi , Do correlations between two input variables reduce the performance of neural network? for example, if we have 5 input variables and two of them has a high coefficent correlation.

Best Answer

Matlab can handle highly correlated inputs. However, if you want to interpret the output in terms of the inputs, you can recursively remove redundant and ineffective inputs from a linear model using STEPWISE or STEPWISEFIT.

Related Solutions

MATLAB: How to minimaze the number of neural network input

Not enough details.

Finding the optimal combination is, in general, complicated. However, using stepwise or stepwisefit on a model that is linear in the variables generally yields a decent approximation.

In addition, if you start with a model that is quadratic in variables with squares and crossproducts but LINEAR IN COEFFICIENTS, the stepwise functions can still be used.

Otherwise, use a backward search with the NN inputs. For example

 1. Train with all
 2. Obtain the responses when each input is separately randomized. 
 3. Remove the variable who randomization degrades the performance the least 
 4. Repeat 2&3 until you can't stand further decreases in performance.

Hope this helps.

Thank you for formally accepting my answer

Greg

MATLAB: Code for regularization of RBF Neural Network

Try NEWFF with RADBAS, PURELIN and MSEREG.