XGBoost vs Human Markets [P]
Mirrored from r/MachineLearning for archival readability. Support the source by reading on the original site.
What is the generally thought of as the upper limit of the predictive power of XGBoost vs an aggregate of humans?
Right now I feed the model the same information that the human market has access to, and the model gets crushed on Top 1 accuracy, it closes the gap a bit but is still 10pp below the market on Top 2 accuracy. Adding the market pricing information to the model does nothing or hurts accuracy compared to just the market pricing.
I'm just feeling really stuck, and I cant seem to be able to tell if I am legitimately at the upper end of what is actually possible with a XGBoost model or if there is some sort of data encoding issue or I just lack enough data.
[link] [comments]
More from r/MachineLearning
-
How can I turn an industry ML project into a publication? [R]
Sep 28
-
Are there any good research papers around Text clustering using LLMs [R]
Sep 28
-
Free, open-source AI engineering course where you build each algorithm by hand: 523 lessons, now as EPUB/PDF books [P]
Sep 28
-
Two-stage shelf audit: YOLO finds the products, embeddings can't tell sibling SKUS apart. What should Stage 2 be? [P]
Sep 27
Discussion (0)
Sign in to join the discussion. Free account, 30 seconds — email code or GitHub.
Sign in →No comments yet. Sign in and be the first to say something.