Recommendation for Machine Learning Interpretability options for a SeriesNetwork object?

Question

Bart Forman 2023-10-11

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编辑： Shivansh 2023-11-8

Hello –

I have a trained algorithm (i.e., LSTM) for time-series regression that is a SeriesNetwork object:

SeriesNetwork with properties:

Layers: [6×1 nnet.cnn.layer.Layer]

InputNames: {'sequenceinput'}

OutputNames: {'regressionoutput'}

I have used some canned routines for machine learning interpretability (e.g., shapley, lime, plotPartialDependence) that work great with some object types (e.g., RegressionSVM) but not with SeriesNetwork objects. The relevant functions I have read about appear to be for use with image classification, e.g., rather than time-series regression.

My question is thus: Can you recommend a machine learning interpretability function for use with a SeriesNetwork object built for regression? I am confident such a function exists, but I can’t seem to find it. Any and all help would be greatly appreciated.

Thank you in advance.