Repository for the DeepSHAP experiments.
- Python, NumPy, Tensorflow, Keras, XGBoost.
Experiments for evaluating baseline distributions are in:
1_multiple_references/
Experiments for evaluating series of models are in:
2_gene_expression_pathway/
3_loss_explanation/
4_feature_extraction/
5_model_stack/
Code underlying the experiments and implementations of DeepSHAP for our specific applications is found in deepshap/
.
The NHANES I, NHANES 1999-2014, CIFAR, and MNIST data sets are all publicly available. The HELOC data set can be obtained by accepting the data set usage license: (https://community.fico.com/s/explainable-machine-learning-challenge?tabset-3158a=a4c37). Metabric data access is restricted and requires getting an approval through Sage Bionetworks Synapse website: https://www.synapse.org/#!Synapse:syn1688369 and https://www.synapse.org/#!Synapse:syn1688370. ROSMAP data access is restricted and requires getting an approval through Sage Bionetworks Synapse website: https://www.synapse.org/#!Synapse:syn3219045 and is available as part of the AD Knowledge Portal https://adknowledgeportal.synapse.org/.