Entropy to calculate information gain for decision tree for classification problems.

Hi

I wonder whether Matlab has the function to calculate the entropy in order to calcuate the information gain for decision tree classification problems, or do I have to write my own entropy function for this purpose. It seems that the default entropy function in matlab is not for this purpose.

Example below:

Without looking at any predictors, just calculate the entropy purely for the target. There are 9 'yes's and 5 'no's in the target. To calcuate the entropy, use the standard equation below. I wonder whether matlab has a function like this to calcuate the entropy?