There's a fantastic paper, Hand 2006, which notes the strong tendency for simple models to get nearly all of the performance possible out of solvable problems.
Hard problems do better with complex algorithms but there's also just less to be gained.
The best solution tends to be simple models applied to the right kind of data such that the problem has become easy. This is sometimes pretty difficult though since the simple models are designed on simple data, which might not always be what you've got.
Hard problems do better with complex algorithms but there's also just less to be gained.
The best solution tends to be simple models applied to the right kind of data such that the problem has become easy. This is sometimes pretty difficult though since the simple models are designed on simple data, which might not always be what you've got.