I’m programming a bot for spanish language and in the pipeline I changed from SpacyFeaturizer to CountVectorsFeaturizer. I don’t know if it is related to the fact that when I do the rasa test, I came across with this graphic:
I found a little weird that there’s no intent prediction wrong and the axis contains negative numbers, I don’t know exactly how to interpret this. When I used the SpacyFeaturizer it looked like this:
Hey @mar, can you check the intent_errors.json file which should’ve been created at the same time (and in the same directory) as the graph? If that file shows no errors for the case when you use CountVectorsFeaturizer, then maybe there really weren’t any mistakes, though it seems a bit odd
Well, these are clear intent prediction errors (apparently, intents criterio11 and criterio12 get confused). If this is really for the case with CountVectorsFeaturizer, then it means that the graph ignores some mistakes, which it shouldn’t. In such case, @mar please report this as a bug on Github and we’ll look into it. However, you might need to provide some minimalistic NLU data version in your report so that we can actually reproduce the bug…