nltk measure the accuracy of the new features
If you don’t have a classified testing set - which allows to measure a performance score, then it is useful to use part of your training data as a validation set, meaning that you test the performance of your model on it (because you have the true labels/values). 

The percentage of the split is arbitrary and depends on the degrees of freedom you have (number of individuals vs number of variables) - 0.1 to 0.25 is a common choice.