You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
The issue MilesCranmer/SymbolicRegression.jl#390 is now resolved. However, the models are extremely slow to train, relatively to others; integration tests on tiny data sets take some minutes (> 10min) apparently due to inappropriate default hyper-parameters for small data.
I propose removing SymbolicRegression altogether from the tests, as not really needed for testing integration. We have plenty of other models of that generic type.
I’m not sure I understand the issue here. Do you mean that the defaults need to be under a certain compute budget as part of the formal interface? But different algorithms have different costs, by their very nature. Maybe there could be a MLJModelInterface.test_defaults(::Regressor) trait to recommend defaults for unit test purposes?
The issue MilesCranmer/SymbolicRegression.jl#390 is now resolved. However, the models are extremely slow to train, relatively to others; integration tests on tiny data sets take some minutes (> 10min) apparently due to inappropriate default hyper-parameters for small data.
I propose removing SymbolicRegression altogether from the tests, as not really needed for testing integration. We have plenty of other models of that generic type.
@MilesCranmer
The text was updated successfully, but these errors were encountered: