Comments (1)
This can also cause an issue in classification (vs regression) on line 64:
https://github.com/andosa/treeinterpreter/blob/master/treeinterpreter/treeinterpreter.py#L64
from treeinterpreter.
Related Issues (20)
- joint_contribution attributes is not documented
- UnboundLocalError of line_shape variable while using ExtraTreeClassifier
- AxisError: axis 1 is out of bounds for array of dimension 1 while using RandomForestClassifier HOT 1
- Getting "ValueError: Wrong model type" when I try to run predict function HOT 2
- 'RandomForestRegressor' object has no attribute 'n_outputs_' needed for the predict function HOT 1
- How is joint contribution calculated over deep tree? How to set max number of elements in joint set, i.e. to doublets or triplets, over a deep tree?
- Should aggregation be the sum over absolute contributions?
- Adding a CITATION file.
- Home page use example code error.
- Performance? HOT 1
- Tests? HOT 2
- Most recent version not installed with pip HOT 1
- Support for pipeline objects
- Python 3.6 + sklearn 0.24 HOT 2
- New release HOT 2
- Minimum python version?
- Error when predicting with a RandomForest that its first trees were trained only on some of the data classes (batched training)
- Does this package work with xgboost model?
- Class order
- No support XGBClassifier ('XGBClassifier' object has no attribute 'n_outputs_')
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