Otherwise, tree ensembles continue to outperform neural networks. The decision tree in the figure shows the winner among the top five methods.
Now, the background:
I explored the why of this question before, but didn’t get very far. This may be expected, given the black-box and data-driven nature of these methods.
This is another study, this time testing larger tabular datasets. By comparing 19 methods on 176 datasets, this paper shows that 𝗳𝗼𝗿 𝗮 𝗹𝗮𝗿𝗴𝗲 𝗻𝘂𝗺𝗯𝗲𝗿 𝗼𝗳 𝗱𝗮𝘁𝗮𝘀𝗲𝘁𝘀, 𝗲𝗶𝘁𝗵𝗲𝗿 𝗮 𝘀𝗶𝗺𝗽𝗹𝗲 𝗯𝗮𝘀𝗲𝗹𝗶𝗻𝗲 𝗺𝗲𝘁𝗵𝗼𝗱 𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝘀 𝗮𝘀 𝘄𝗲𝗹𝗹 𝗮𝘀 𝗮𝗻𝘆 𝗼𝘁𝗵𝗲𝗿 𝗺𝗲𝘁𝗵𝗼𝗱, 𝗼𝗿 𝗯𝗮𝘀𝗶𝗰 𝗵𝘆𝗽𝗲𝗿𝗽𝗮𝗿𝗮𝗺𝗲𝘁𝗲𝗿 𝘁𝘂𝗻𝗶𝗻𝗴 𝗼𝗻 𝗮 𝘁𝗿𝗲𝗲-𝗯𝗮𝘀𝗲𝗱 𝗲𝗻𝘀𝗲𝗺𝗯𝗹𝗲 𝗺𝗲𝘁𝗵𝗼𝗱 𝗶𝗺𝗽𝗿𝗼𝘃𝗲𝘀 𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗺𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝗰𝗵𝗼𝗼𝘀𝗶𝗻𝗴 𝘁𝗵𝗲 𝗯𝗲𝘀𝘁 𝗮𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺.
This project also comes with a great resource. This time it comes with a ready-to-use codebase and testbed along with the paper.