[ML] add LGBMClassifier transform support #252
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benwtrent
added
enhancement
benwtrent
commented
Aug 11, 2020
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| def random_rows(data, size): | |||
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this provides MUCH better testing.
The training data is random, and selecting a random subset to infer against provides much better coverage than a static two rows.
sethmlarson
approved these changes
Aug 12, 2020
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@sethmlarson i don't think so. Much of the logic formatting is exactly the same as xgboost. The node extraction is just slightly different. |
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Great! I'll merge this then :) |
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Adds support for transforming LGBMClassifier models.
We are able to support binary, multiclass, and multiclassova. These are the only valid ones for classification.
But, still restricting to prevent a regression where lightgbm adds a new objective without us knowing.