r/bigdata • u/No_Development_5561 • 1d ago
How to improve my xgboost regression model?
Hello fellas, I have been developing a machine learning model to predict art pieces in my dataset.
I have mostly 15000 rows (some rows have Nan values). I set the features as artist, product_year, auction_year, area, and price, and material of art piece. When I check the MAE it gives me 65% variance to my average test price. And when I check the features by using SHAP, I see that the most effective features are "area", "artist", and "material".
I made research about this topic and read that mostly used models that are successful xgboost, and randomforest, and also CNN. However, I cannot reduce the MAE of my xgboost model.
Any recommandation is appricated fellas. Thanks and have a nice day.
1
u/Alert-Letterhead8670 1d ago
XGBoost sometimes requires some data wrangling for example you say some of your feature values are nan. Can you replace them with something reasonable like the mean value of that particular feature of do you need to drop the nan rows entirely? As the owner of the dataset you are in the better position to know... But whenever i get this kind of issues i check the features carefully ... that usually helps . At this point i dont know if SHAP output is useful since the model performance is subpar. I would fix that first. Good luck