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Fit interpretable models. Explain blackbox machine learning.

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Unable to show multiple ExplanationDashboard in the same notebook when running multiple EBM models. Only the first model shows the ExplanationDashboard while others not shown.

bug

Hi, With this lines of code `dp_ebm = DPExplainableBoostingClassifier(epsilon=1, delta=1e-5) # Specify privacy parameters dp_ebm.fit(train_df[features], train_df[target])` I am getting this Type error. Any ideas on how to fix this? `---------------------------------------------------------------------------...

Hello! Have the features mentioned here to expose FAST results to the user been implemented in some fashion? The method listed here does not work, and I would like to...

Hello, is it possible to use custom error metrics/loss functions (such as mean Poisson Deviance from the sklearn package) for our model builds? My dataset has a poisson distribution which...

I am building a docker image and one of the commands lists interpret like this ```Dockerfile RUN mamba install -c interpretml interpret -y ``` I take it this context is...

Hi @interpret-ml @richcaruana @Harsha-Nori , It is very fun using Interpret ML which is defining explanations in a very clean and smooth manner . But I have very few doubts...

Hi , Can anyone leave a link here for accessing the Logistic Regression(Explainability) Source code . I am having few doubts also : 1 : How intercept is calculated ?...

Hello, Thank you for making this great package! I'd like to know if we can compute the p-value of a given score/weight (logit from EBM global explanation) from a two-tailed...

The size of my dataset is (150, 32) and the y-label is (150, ) I don't get an error with the open source dataset on your package, but I get...

Hi, Is there any particular paper or tutorial which clarifies the mathematical calculation behind the scores if yes,please provide as I am unable to crack the source code . Please...