Recommend pickling as the way to save XGBClassifier / XGBRegressor / XGBRanker #3829
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…XGBRanker The `save_model()` and `load_model()` method only saves the part of the model that's common to all language interfaces and do not preserve Python-specific attributes, such as `feature_names`. More crucially, label encoder is not preserved either; this is needed for the scikit-learn wrapper, since you may have string labels. Fix: Explicitly recommend pickling as the way to save scikit-learn model objects.
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On a longer term, let's consider migrating to an extensible model format to store auxiliary information: JSON, Protocol Buffers, or INI config. LightGBM uses INI-like format, which works well for them. |
Codecov Report
@@ Coverage Diff @@
## master #3829 +/- ##
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+ Coverage 51.86% 52.06% +0.19%
Complexity 203 203
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Files 181 181
Lines 14358 14358
Branches 495 495
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+ Hits 7447 7475 +28
+ Misses 6673 6645 -28
Partials 238 238
Continue to review full report at Codecov.
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CodingCat
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Oct 25, 2018
…XGBRanker (dmlc#3829) The `save_model()` and `load_model()` method only saves the part of the model that's common to all language interfaces and do not preserve Python-specific attributes, such as `feature_names`. More crucially, label encoder is not preserved either; this is needed for the scikit-learn wrapper, since you may have string labels. Fix: Explicitly recommend pickling as the way to save scikit-learn model objects.
alois-bissuel
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Dec 4, 2018
…XGBRanker (dmlc#3829) The `save_model()` and `load_model()` method only saves the part of the model that's common to all language interfaces and do not preserve Python-specific attributes, such as `feature_names`. More crucially, label encoder is not preserved either; this is needed for the scikit-learn wrapper, since you may have string labels. Fix: Explicitly recommend pickling as the way to save scikit-learn model objects.
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The
save_model()andload_model()method only saves the part of the model that's common to all language interfaces and do not preserve Python-specific attributes, such asfeature_names. More crucially, label encoder is not preserved either; this is needed for the scikit-learn wrapper, since you may have string labels.Fix: Explicitly recommend pickling as the way to save scikit-learn model objects.
Related issue: #3828