Gaurav Gupta

@DBrughmans, can you paste the error or the stack trace here?

@DBrughmans can you paste the error or the stack trace here so that we can make progress on this issue?

Hi @msank00, Thanks for trying out the package. There are no plans as yet. Creating a conda package would require our dependencies to be also installable via conda and have...

@djlwzw, the num_output_nodes is internal to DiCE nd represent the number of classes in a classification problem. Whis version of dice-ml are you using in your environment? Regards,

@djlwzw could you close this issue if you are unblocked? Regards,

@PaoloFantine there are no parameters like 'continuous_features', 'instance', 'model', 'backend' in the `generate_counterfactuals` method. Could you may be use the sample notebooks from https://github.com/interpretml/DiCE/blob/master/docs/source/notebooks/DiCE_getting_started.ipynb to correct the above code?

We should be respecting the range. If you could share a sample notebook and dataset, it will be possible for us to dig into this issue. Regards,

@tonyabracadabra, You can do something like this below:- ``` exp.generate_counterfactuals( query_instances=sample_custom_query_1, total_CFs=10, desired_class=desired_class, desired_range=None, permitted_range={'Categorical': ['A', 'B', 'C']}, features_to_vary='all') ``` That should be a signal to dice to use only...

@londumas does some sample of the query_instance has a missing value? I think if dice-ml doesn't handle this scenario it is ok. Shouldn't the user woryy about supplying a legitimate...

@prunprun, could you paste the error that you saw with DicePytorch? Regards,