The Ultimate Guide to Cognigy NLU Training
The Ultimate Guide to Cognigy NLU Training
Authors name: Sebastian Glock February 14, 2022
Many of our customers have utilized the Intent feedback analyzer to continuously improve their NLU models with tremendous success. However, at Cognigy, we are regularly asked about a more systematic approach to Intent training in projects.
So, we created a comprehensive tutorial to present a systematic technique that can be employed during the project planning process.
Visit our Help Center Article to delve deep into a systematic approach to Intent training.
In the article, you'll learn about the phases that can be used to outline the intent creation/training process:
Introduction
Improving Intent recognition
- Machine learning
- Cognigy Script
Resolving Intent conflicts
- Moving Example Sentences to the better-suited Intent
- Moving Intents into a hierarchy
- Merging multiple Intents into one
- Outsourcing Intents to a separate Flow
- Adjusting the NLU settings
Reducing false positives
- Machine learning / Reject Intent
- Adjusting the NLU settings