Divide and Conquer

Subdividing larger intents into a variety of types the classified can understand

Helpful core doc references:

• Active learning sampling
• Semantic clustering

🦸 SuperPower Objectives :

• Strengthen an existing large intent using the active learning loop from our unlabelled data
• Use the similarity to check we've gone wide enough
• SubDivide the large concept into more granular ones
• Check we've included from the parent all the data we need
• Check that all the data from parent is in a sub intent
• Repeat subdividing children as much as you need
• Strengthen any individual children short of examples to ensure have 6+ for each
• At any point look again at your unlabelled data using any parent or child in the hierarchy
• Show how we immediately have a strong f1 score even from the first k-fold because we built in harmony with our classifier.

Video Example

17 minutes - yes a bit long, but really key!