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Thanks for your outstanding work. But I have a few questions about your code.
1. In Fig. 4 in your paper, the LSTM encoders (i.e. the `AtCAF.uni_acoustic_enc` and `AtCAF.uni_visual_enc`) take the d…
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I am working on a multi-label classification task. Most of the feature values are zero. The dataset is a binary vector. When I tried to generate the counterfactual, I got the error like sparse array …
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This is perhaps a meta-proposal which may be fully addressed by multiple separate PR's. But the core idea is to build out the functionality (and visibility of that) on the causal inference side. So th…
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Hi,
Very nice work. Thank you for your contribution.
At the step where we feed in "Custom" covariate models, I am interested in providing custom fit and predict functions. I see from the source co…
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I am trying to generate Counterfactual Explanations for a NeuroTreeModel, also trained using `CounterfactualExplanations.jl`. While the model itself seems to work as expected (i.e., it is able to gene…
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Hi team,
First of all, thanks to the team for working on building such a good package for us to use.
I follow the example _Counterfactual with Reinforcement Learning (CFRL) on Adult Census_ to …
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AttributeError Traceback (most recent call last)
/tmp/ipykernel_34754/2258094842.py in
----> 1 ResponsibleAIDashboard(rai_insights, cohort_list=cohort_list)
~/.conda/e…
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So far, in DelayedSaturatedMMM, there is no way to extract channel contributions on other than data used for fitting.
I'd like to extract channel contributions on any input data, for example, future …
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Thank you for all your hard work.
I've noticed that in your implementation of classifiers in `ClassificationEvaluator`, it seems that classifiers like `LogisticRegression` and `kNN` are [trained o…
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I am working on a heart disease dataset which has continuous variable as a treatment (thalach) and outcome categorical(target).There is another variable that the treatment affects (exang) which is cat…