Awesome work on the library. I have discovered it recently and it seems to have a lot of good features.
I wanted to try it out for tree structured data (Abstract Syntax Trees). I have trained a network called TBCNN. I want to check which nodes in the tree are causing the prediction to be 1 or 0.
My data is stored as a list of dictionaries, where each (nested) dictionary represents a data point (specifically a tree)
[{'node': 'ci_root', 'children': [{'node': 'ci_class_decl', 'children': [{'node': 'ci_modifiers', 'children': [{'node': 'ci_modifier', 'children': []}]}, {'node': 'ci_type', 'children': [{'node': 'SimpleType', 'children': [{'node': 'SimpleName', 'children': []}]}]}, ... ]
NOTE: This is just a part of one data point.
Also, I use word2vec style embeddings for each node.
Is there any way in which I can use the tool to identify the nodes affecting the prediction?
Awesome work on the library. I have discovered it recently and it seems to have a lot of good features. I wanted to try it out for tree structured data (Abstract Syntax Trees). I have trained a network called TBCNN. I want to check which nodes in the tree are causing the prediction to be 1 or 0.
My data is stored as a list of dictionaries, where each (nested) dictionary represents a data point (specifically a tree)
[{'node': 'ci_root', 'children': [{'node': 'ci_class_decl', 'children': [{'node': 'ci_modifiers', 'children': [{'node': 'ci_modifier', 'children': []}]}, {'node': 'ci_type', 'children': [{'node': 'SimpleType', 'children': [{'node': 'SimpleName', 'children': []}]}]}, ... ] NOTE: This is just a part of one data point.
Also, I use word2vec style embeddings for each node.
Is there any way in which I can use the tool to identify the nodes affecting the prediction?
Thank you