We don’t have any citations for the RadialDistributionFunction because there isn’t a paper that emphasizes its use for ML and I’m not sure what paper introduced it in general.
If you use the featurize function to compute the distribution function, it will produce a vector of values you can use as an input to an ML algorithm. Unless I misunderstand your question, it should not be necessary to reduce it to a single value to train a ML model with scikit-learn.
I have an example using the Partial Radial Distribution function, but would not be able to send it to you until I’m back from travel. Would that be useful for you?
On Tue, Aug 27, 2019, 9:31 AM genie [email protected] wrote:
Are there any citations for RadialDistributionFunction featurizer? I’m looking to use dictionary returned by this featurizer to predict energy band gap values. But not sure how to reduce distances, distribution key( values for them are 200 length list ) values to single number so as to use in prediction.
Any pointers would be helpful
Thank you in advance
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