leaves
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dmitryikh
pure Go implementation of prediction part for GBRT (Gradient Boosting Regression Trees) models from popular frameworks
we have `internal.pickle` package to read pickle format. It's difficult to debug what was read into the memory. We need a function to print parsed pickle data for debug purpose.
https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.GradientBoostingRegressor.html
https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestRegressor.html
https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html
Currently, leaves uses a standalone matrix implementation that's almost completely binary compatible with gonum/mat.Dense implementation. It would be very beneficial to just use the one from gonum/mat. (Or, at least,...
This internal package makes quite extensive use calls to 'binary.Read'. This is very slow as it makes heavy use of reflection. One should use the binary.ByteOrder.PutUintXX and binary.ByteOrder.UintXX methods instead.
I have a model trained withtweedie regression in light gbm. With leaves I got panic: ``` panic: unexpected objective field: 'tweedie' ``` It works perfectly in python's lightGBM [lgbmodel_ww.txt](https://github.com/dmitryikh/leaves/files/9581498/lgbmodel_ww.txt)
