- Allows ordering_keys to be given to force_plot courtesy of JasonTam - Fixes sparse nonzero background issue with KernelExplainer courtesy of imatiach-msft - Fix to support tf.concat in DeepExplainer.
0.25.1
Fixes a problem where tree_shap.h was not included in the pip bundle.
0.25.0
- Support for PyTorch in GradientExplainer and preliminary support for PyTorch in DeepExplainer courtesy of gabrieltseng. - A matplotlib version of the single sample force_plot courtesy of jverre. - Support functional Keras models in GradientExplainer. - KernelExplainer speed improvements. - Various performance improvements and bug fixes.
0.24.0
New improvements include: Faster KernelExplainer execution for sparse inputs. Support for sklearn gradient boosting classifiers. DeepExplainer extended to support very deep models.
0.23.1
This fixes numerical stability issues with the softmax operator for DeepExplainer. It also fixes a minor alignment issue with image_plot.
0.23.0
This release includes a nice update courtesy of imatiach-msft for KernelExplainer. KernelExplainer now runs faster and supports sparse data matrices!
We have also refactored DeepExplainer and made it compatible with TensorFlow 1.10. There are still a few issues to track down, but DeepExplainer is getting more complete :)