My wife’s sambar tastes different from my mother’s. And mine, too. When I cooked as a bachelor, my neighbour would pop by, taste the sambar, and exclaim, “Rasam super!” Surbhi’s Day 5 of the 30-day challenge was about Sambar which inspired me to take her dataset and create a decision tree for which state a sambar recipe is from based on its ingredients. ChatGPT started with 68 recipes and built a tree at 41% accuracy. As we added more recipes: ...
This is my decision tree for which model to use on #ChatGPT right now. O𝟯: Use by **default. O**𝟰-mini-high: Use when **coding. GPT** 𝟰o: Use for a quick response or to create image. LinkedIn
I talked about my approach for multicriteria decision-making, and mentioned that it was fundamentally flawed. Here’s why. The charts above compared two industries. The bigger the area, the more favourable the industry. The underlying assumptions being: The criteria are comparable. (Points at the same level are of comparable importance. Twice as large is twice as important.) All (and only) relevant criteria have been included. In this particular example, I know for a fact that both these assumptions are invalid. And in every case I used this methodology, the assumptions fail. ...