Not getting predited_probability for counterfactuals using RandomForest Classifier

[vdesai24]

Hi,

I am trying to generate counterfactuals for a classification model. Trained the model using RandomForestClassifier. I am expecting the target variable should show the predicted probability. It is showing predicted class instead. What changes do I need to make to give me the predcited probabilities in the generated counterfactuals. Below is the code to generate counterfactuals: model = RandomForestClassifier() d = dice_ml.Data(dataframe=train_dataset, continuous_features=['age', 'hours_per_week'], outcome_name='income') m = dice_ml.Model(model=model, model_type='classifier',backend="sklearn") exp = dice_ml.Dice(d, m, method="random")

e1 = exp.generate_counterfactuals(x_test[0:1], total_CFs=5, desired_class='opposite') e1.visualize_as_dataframe(show_only_changes=True)

Output:

I need predicted probabilities instead of the predicted class in the outcome.

[gaugup]

@vdesai24, the output for the counterfactual is currently only shows the desired_class which is either 0 or 1. We could add another column which can contain the probabilities of the target class in classification scenario.

@amit-sharma what do you think about adding additional column for adding probabilities in classification scenarios?

Regards,

[amit-sharma]

yes, that's a good idea. We just need to call the classifier again on the returned CF data to obtain the predicted probabilities. This would be a general solution that can work for any CF method. For efficiency, we may make it as an optional flag, so that this additional computation is not done.

[vdesai24]

Hi, Thanks, when can I get this enhancement in the package.

Regards,

[amit-sharma]

We will have to see how to prioritize this change, given the other enhancements we are working on. Hopefully this will be included in the next release, near Dec.

[vdesai24]

Thanks @amit-sharma

[LingAdeu]

Hi @amit-sharma may I know if this enhancement has been updated? Thanks!