Karndeep Singh
Video Demonstrate the use of model explainability and understanding of the importance of the features such as pixels in the case of image modeling using SHAP Framework.
Notebook Link:https://github.com/karndeepsingh/Explainable-Ai
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Can you plz suggest some explainable library for time series…
Thanks a lot, for the video. very useful 🙂
Very Helpful. Thanks
Does shap has R package ?
Thanks for the tutorial, which versions of SHAP and keras are you using?
The feature values are there, i am using the decision tree to predict the label as 0 or 1. but instead the decision tree should predict the output in the range of [0,100] like score. is it possible to get this using SHAP?
I saw this error – "keras is no longer supported, please use tf.keras instead. Your TensorFlow version is newer than 2.4.0 and so graph support has been removed in eager mode. See PR #1483 for discussion."
How did you resolve this? I have built LSTM model for my sequential data and tried to explain the model using SHAP but got the same error. Please help.
Great content! Thank you!
How much time does the whole code take to run?
I want to run this code in my dataset but I couldn't done it. Can you help to solve it or any suggestions How can I solve it? (How Can I connect Drive) or need annotation ?