MATLAB: Is possible to normalize just the training data instead of the whole data using Neural Network toolbox

neural networknormalizaition

Using the Matlab functions, it is possible to normalize the input and output data that will feed the Neural Network. However, is possible to just normalize the training data instead of the whole data set? Is this a better approach than normalizing the whole data?

Best Answer

The normalization parameters ARE obtained from the training subset; then applied to all of the data.

So, you have no problem!

Hope this helps.

Greg

Related Solutions

MATLAB: Do I need to normalize data when using patternnet or Matlab will take care of it

BY DEFAULT: All of the neural network training algorithms normalize inputs and targets to [ -1 1 ] AND denormalizes the output using the parameters of the target normalization.

Why in the world would you substantially deviate from the examples in the documentation

 help patternnet

and

 doc patternnet ?

The first thing you should do is to use the documentation code in a loop with multiple random weight initializations.

Next use a double loop approach where the outer loop systematically increases the number of hidden nodes.

I have posted zillions of single and double loop examples in both the NEWSGROUP and ANSWERS. You can begin searches with

                                      HITS
                              NEWGROUP    ANSWERS
 greg patternet                    60       451

and

 greg patternnet tutorial          14        44

In particular note that most cases only involve searches over number of hidden nodes and initial random weights.

Although there are some cases of m-fold cross validation, the index bookkeeping is so tricky it tends to be far less fruitful than straightforward multiple uses of the default DIVIDERAND.

Hope this helps.

Thank you for formally accepting my answer

Greg

MATLAB: When I generate a Matlab function of a neural network, it comes with the normalization/re-normalization constants. Will these constants affect the neural network performance on another data set? Why

Not if both datasets have similar summary statistics (e.g., mean/std for mapstd or min/max for mapminmax).

That is why sometimes it is better to explicitly normalize before training and explicitly denormalize after training.

Hope this helps.

Thank you for formally accepting my answer

Gregg

Best Answer

Related Solutions

MATLAB: Do I need to normalize data when using patternnet or Matlab will take care of it

MATLAB: When I generate a Matlab function of a neural network, it comes with the normalizat​ion/re-nor​malization constants. Will these constants affect the neural network performance on another data set? Why

Related Question

MATLAB: When I generate a Matlab function of a neural network, it comes with the normalization/re-normalization constants. Will these constants affect the neural network performance on another data set? Why