Misc fixes for default-constructibility of our learners #144
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That will give some of the scikit-learn estimator API (such as set_params and get_params) for free.
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Removing the regularizer default overrides is a small breaking change (analogous to #142). |
Codecov Report
@@ Coverage Diff @@
## master #144 +/- ##
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+ Coverage 60.08% 60.11% +0.03%
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Files 116 116
Lines 7662 7668 +6
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+ Hits 4604 4610 +6
Misses 3058 3058
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Code coverage is only decreasing because of the |
kiudee
requested changes
Jul 1, 2020
Tuples are immutable and the scikit-learn estimator API requires estimator parameters to be immutable (to make cloning work properly). Since we do not use the parameters in a mutable way, this doesn't make a difference.
In the spirit of 2291f86.
Scikit-learn requires unmodified storage of estimator parameters. Instead, parameter validation and initialization should be deferred to fit, which we do here by moving it into the model creation.
Scikit-learn mandates that all estimator arguments should be stored in an instance attribute of the same name.
timokau
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Thanks for the feedback, I addressed all your comments. Please have another look. |
kiudee
approved these changes
Jul 1, 2020
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Description
Pulling out the changes of #116 that are ready for merge now. As I said in #116 (comment), this brings us very close to passing the "default-constructible" test. I think/hope that will be the highest hurdle for sklearn api compatibility.
Outstanding issues are the kernel-regularizers and scikit-learn/scikit-learn#17756.
Motivation and Context
See #116.
How Has This Been Tested?
Linters & tests.
Does this close/impact existing issues?
Impacts #116, but doesn't close it.
Types of changes
Checklist: