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Don't Allow Infeasible Hyperparameter Combinations #26

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epeters3 opened this issue Apr 14, 2020 · 0 comments

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bug 🐛

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epeters3 commented Apr 14, 2020 •

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In the logistic regression solver, this hyperparameter combo is not supported, so make sure it cannot be tried in skplumber:

  File "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_logistic.py", line 445, in _check_solver
    "got %s penalty." % (solver, penalty))
ValueError: Solver lbfgs supports only 'l2' or 'none' penalties, got elasticnet penalty.

Here is another one for SVM:

  File "/usr/local/lib/python3.6/dist-packages/sklearn/svm/_base.py", line 793, in _get_liblinear_solver_type
    % (error_string, penalty, loss, dual))
ValueError: Unsupported set of arguments: The combination of penalty='l1' and loss='squared_hinge' are not supported when 
dual=True, Parameters: penalty='l1', loss='squared_hinge', dual=True

The text was updated successfully, but these errors were encountered:

epeters3 added the bug 🐛 label

epeters3 changed the title ~~Don't Allow Hyperparameter Combination~~ Don't Allow Infeasible Hyperparameter Combinations

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