Added more of the sklearn regressors to the presets #27
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reiinakano
reviewed
Jun 7, 2017
xcessiv/presets/learnersetting.py
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| 'sklearn_GP_regressor', | ||
| 'sklearn_ridge_regressor', | ||
| 'sklearn_lasso_regressor', | ||
| 'sklearn_kernelRidge_regressor', |
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stylefix: probably better to use sklearn_kernel_ridge_regressor
reiinakano
reviewed
Jun 7, 2017
xcessiv/presets/learnersource.py
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| sklearn_knn_regressor_source = \ | ||
| """from sklearn.neighbors import KNeighborsRegressor | ||
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| base_learner = KNeighborsRegressor(random_state=8) |
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I don't think KNN has a random_state parameter. Please also double check the other estimators to see if they have a random_state parameter.
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Looks good so far! Just made a few comments that should be addressed first. |
…equire it, and renamed 'kernelRidge' to 'kernel_ridge'
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Think it looks good! Am a bit scared of pulling these without adequate unit tests, but I guess it's my fault for not writing them in the first place. I really need to get to doing those. Thanks a lot! |
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no problem :) if you'd like, I can start having a look at writing these tests? |
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@enisnazif That would be very helpful! :) |
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Added the large majority of the more popular regressors of sklearn. I am aware that a few may be missing. Also, I tidied the code slightly and split the regressors and classifiers into two sections.