but that seems like a shortcoming of current autointerp/feature-label scoring methods. we def need better scoring methods—would be interested in proposals/submissions for this.
My feeling is that the biggest shortcoming of current scoring methods is assuming all features are created equal. An alternative would be to first classify the feature, using something like the correlation score I propose, and then score the label with a category-specific method.
What’s your opinion on the proposed categories ?
and i’d be curious about the next step eg code that does the new proposed feature labeling method, plus side by side examples
Sure, I’m gonna run an attribution graph experiment this week, trying to use such a proposed labeling method and share the results here
My feeling is that the biggest shortcoming of current scoring methods is assuming all features are created equal. An alternative would be to first classify the feature, using something like the correlation score I propose, and then score the label with a category-specific method.
What’s your opinion on the proposed categories ?
Sure, I’m gonna run an attribution graph experiment this week, trying to use such a proposed labeling method and share the results here