Comments (4)
Hi.
For question 1:
Yes, it's right. In fact, drugA-drugB is the same as drugB-drugA in this project, we just delete half of interactions to reduce the replication. However, if you try to use Knowledge Graph, the order will make a difference. It means (drugA,relation,drugB) is different from (drugB,relation,drugA). We need to determine the order with dependency relationship.
For question 2:
The original fingerprint is 881 dimension. We perform encoding again toward the results of the 881 dimension again so it results in 583. You can have a look on the table "drug" and column "smile". The maximum number is 881.
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If we want to reproduce the results in your paper or develop our own method, should the dataset keep 37264 in this repo or aug to 74528? But the latter may cause a different split and test set ...
from ddimdl.
I think you should keep 37264, because it may be easier for the model to predict (drugB,drugA) if (drugA,drugB) already exists in the training set. This will lead to false high accuracy.
from ddimdl.
OK, understand. Thanks for your answer~
from ddimdl.
Related Issues (20)
- NLPProcess running error HOT 4
- KeyError: 'DB00001' HOT 5
- Smiles Didn't extracted using DRKG_drug_spider.py HOT 6
- Input shapes for LSTMS HOT 4
- table 2 results in paper HOT 3
- 关于数据集的问题 HOT 2
- Request Full Code of 3 Tasks for Further Study HOT 5
- Request full code HOT 2
- about the the running rounds
- Fingerprints
- Ask for the DDI types of Devision HOT 4
- 关于数据处理的问题 HOT 1
- Request full code
- i need some help in testing the model after get files
- i need some help in testing the model after get files model.h5 and smile+target+enzyme_each_DDIMDL.csv
- problem in test the model
- task2 and task3
- error related to sklearn.linear_model.logistic
- Database connectivity issue
- NLP_Process
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