EasyEnsembleGeneralization #4
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chkoar
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| random_state = check_random_state(self.random_state) | ||
| estimator_seeds = random_state.randint(MAX_INT, size=self.n_estimators) | ||
| sampler_seeds = random_state.randint(MAX_INT, size=self.n_estimators) |
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I think that we should use the _set_random_states from the ensemble.base.py
https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/ensemble/base.py
| pipelines = [] | ||
| seeds = zip(estimator_seeds, sampler_seeds) | ||
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| for i, (estimator_seed, sampler_seed) in enumerate(seeds): |
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If the random state is properly done before, we could do that in parallel with joblib
| sampler = clone(self.base_sampler_) | ||
| sampler.set_params(random_state=sampler_seed) | ||
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| if hasattr(self.base_estimator_, 'random_state'): |
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We should reuse make_estimator?
https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/ensemble/base.py#L119
| for i, (estimator_seed, sampler_seed) in enumerate(seeds): | ||
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| sampler = clone(self.base_sampler_) | ||
| sampler.set_params(random_state=sampler_seed) |
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we should create a make_sampler similarly to make_estimator
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| from ..pipeline import Pipeline | ||
| from ..under_sampling import RandomUnderSampler as ROS | ||
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I would use the full name since we are using it once :) Might be more intuitive and this is a burden to right it once.
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@glemaitre since |
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For the remaining error, it could because we creating a meta-estimator which should not go through the same common test than estimator: |
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@glemaitre I can think two optionn right now:
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We should be able to monkey patch as well. But I would go for 1. for the moment |
I didn't mention that, in purpose, cause I thought that you wont like this approach. |
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If this is very small patch, I am for it ;)
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Codecov Report
@@ Coverage Diff @@
## master #4 +/- ##
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- Coverage 98.32% 98.31% -0.01%
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Files 68 70 +2
Lines 3879 3975 +96
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+ Hits 3814 3908 +94
- Misses 65 67 +2
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chkoar
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chkoar
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@glemaitre I was thinking that I could proceed to the experiments using this implementation. Any suggestions are welcome.