Are there any performance penalizations because of this? The code for the state machine looks very complex and I'm curious about what's the difference in terms of performance between the pyramid model or the flat model.
What are other metrics that can help validate the F1 score? I'm asking because I believe having a small sample size can skew the number or hide a flaw in the classification algorithm it's scoring.
In other words, what else should I ask to validate that a 70% F1-score is better than a 90% F1-score but on a smaller data set?
Funny how Software updates make me more excited than Hardware ones... I'm so excited for iOS 12!
Also, iOS on Mac OS! I wonder what this means for the React Native devs... I have no experience on that platform but I'm curious about the potential impact of iOS + MacOS on that community
Very fun to read but may be too advanced to start with... is there a particular reason why I couldn't or should't run this on a regular core i7 7700k powered machine?
When you talk about discerning between algorithms from Google, Stanford, etc... what's the criteria for doing that? Does it change based on the domain? if you are just trying to classify feedback how much the domain affects the algorithm?