𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗻𝗴 𝗖𝗼𝗻𝗱𝗶𝗶𝘁𝗶𝗼𝗻𝗮𝗹 𝗣𝗿𝗼𝗯𝗮𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀
Bayesian Networks help you predict outcomes. They rely on Conditional Probability Tables. Experts often struggle to fill these tables. Giving exact numbers is hard. This is the knowledge acquisition problem.
You face these issues:
- Tables grow too large.
- Experts lack exact data.
- Manual entry takes too long.
New methods fix this. You generate probabilities with better tools. Your models get more accurate. You save time.
Optional learning community: https://t.me/GyaanSetuAi