Skater
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oracle
Python Library for Model Interpretation/Explanations
when i tried to install "Skater" on my macbook with pip i got this error, anyone have ideas how to fix this? thanks.. (my environment is python 3.7.4) Building wheels...
Installing `skater==1.1.2` with pip on Python 3.6.8 generates the following warning. It sounds like this will turn into an issue with the release of pip 20.2. > DEPRECATION: skater==1.1.2 from...
Hello I am having this issue with installation of Skater. I have seen similar errors [this](https://github.com/oracle/Skater/issues/287) and [this](https://github.com/oracle/Skater/issues/286) however my error comes from python3.6, I am reporting it as a...
I'm trying to run the **examples/rule_lists_titanic_dataset.ipynb** I've found a couple of problems which I was able to resolve by doing minor modifications of the code. Unfortunately, I can't pass this...
I am doing comparative analysis of all X-ML frameworks- ( aix360, skater, eli5, alibi, h20, ms interpreter, ethical ml, Dalex) . Is there any presentation, doc, video to understand all...
I am running the plot_feature_importance in a jupyter notebook (python 3.6, skater-1.1.2) but it got stuck without providing any error. Code is the following ``` interpreter = Interpretation(training_data=X_train_XAI, feature_names=data.drop(columns=col_emb).columns) im_model...
This ticket is to extend the coverage for supporting natively interpretable models(_Rule-based model_). Interpretable Decision sets are similar to Bayesian Rule List(BRL) in-terms of the human understandable IF-ELSE conditional statements....
To allow the users the flexibility to install either from pip or conda, its important that we maintain consistency on both package managers.
I added a keras custom layer as the RBF middle layer of my RBFN.. Feature Importance technique worked fine but plot_partial_dependence gave the error of unknown layer RBF layer in...
Hey all, I've had to step away from this project for some time, but I'd love to step back into it and start contributing again. I thought I'd begin by...
