Having Different Results Every Run With Gmm Classifier

I'm currently doing a speech recognition and machine learning related project. I have two classes now, and I create two GMM classifiers for each class, for labels 'happy' and 'sad'

Solution 1:

But every time I run the script I am having different results. What might be the cause for that with same test and train samples?

scikit-learn uses random initializer. If you want reproducable results, you can set random_state argument

random_state: RandomState or an intseed (None bydefault)

for name, data in training.iteritems():

This is not correct since you train only on a last sample. You need to concatenate features per label into a single array before you run fit. You can use np.concatenate for that.