Comments (1)
Unfortunately tfdf currently does not support local interpretation methods like SHAP out of the box. If you our anyone else wants to push integrating TF-DF or YDF with SHAP's TreeExplainer, we'd be happy to provide assistance with design and implementation.
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Related Issues (20)
- 'use_predefined_hps' auto-tuning failure for RANKING tasks HOT 7
- Multi-target regression - one model or multiple submodels HOT 1
- Faild in multi-class classification HOT 4
- incorrect regex causes injection of tensorflow during build to fail
- Installation with Fedora 38 HOT 1
- FULL_COMPILATION=0 does not build all necessary targets HOT 7
- label not found in tfdf.keras.pd_dataframe_to_tf_dataset HOT 3
- Sample numerical uplift HOT 3
- Best practice for installation via poetry using M1 mac (arm chip) HOT 2
- model_plotter.plot_model_in_colab has No response HOT 3
- How to use tfdf.builder.CARTBuilder to build/train a decision tree by hand HOT 19
- Models trained with fit_on_dataset_path behave unexpectedly HOT 2
- Models trained on pure 1's predict 0 HOT 3
- max_vocab_count won't work for CATEGORICAL integerized in tfdf.keras.GradientBoostedTreesModel HOT 5
- Save and load model with tunning in automatic_tuning_colab.ipynb HOT 4
- Symbol not found, but versions are compatible according to the website HOT 4
- Loading a model returns either an untrained model or broken model HOT 1
- Using call_get_leaves inside @tf.function call in ensemble model inherits from tensorflow.keras.Model HOT 10
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