Preprocessing as a binary treatment: you have two treatments and we can observe the counterfactual by applying both kinds of preprocessing to the data
treatment 0 (control): processed with word2vec
- Y_0 or Y(0) potential outcome if processed with word2vec
treatment 1: processed with doc2vec
- Y_1 or Y(1) potential outcome if processed with doc2vec
Causal effect evaluates what would happen if you use doc2vec instead of word2vec
For any individual requirement, we can observe
- Does it accurately trace the requirement regardless of which preproc you use, so No effect
- Does it inaccurately trace the requirement regardless of which preproc you use, so No effect
- Traces requirement with word2vec but not doc2vec, so Negative effect
- Traces requirement with doc2vec but not word2vec, soPositive effect
We compute the average of this result for every requirement
ACE=E[Y_1 ]−E[Y_0 ]
#109
Preprocessing as a binary treatment: you have two treatments and we can observe the counterfactual by applying both kinds of preprocessing to the data
treatment 0 (control): processed with word2vec
treatment 1: processed with doc2vec
Causal effect evaluates what would happen if you use doc2vec instead of word2vec
For any individual requirement, we can observe
We compute the average of this result for every requirement
ACE=E[Y_1 ]−E[Y_0 ]
#109