search

reml-lab / mTAN

Code for "Multi-Time Attention Networks for Irregularly Sampled Time Series", ICLR 2021.
MIT License
110 stars 22 forks source link

Results are not reproducible on MIMIC-Ⅲ #3

Open ChongWang2000 opened 2 years ago

ChongWang2000 commented 2 years ago

I use the data extraction process to get the MIMIC-Ⅲ dataset which contains 53,211 records. I use the given code to split the train, valid and test set. And I use the hyperparameters given to run mTAN-full, but I do not achieve 0.8544 AUROC on MIMIC-Ⅲ dataset . The highest is AUROC ~0.838.

This is achieved with this command: python3 tan_classification.py --alpha 5 --niters 300 --lr 0.0001 --batch-size 128 --rec-hidden 256 --gen-hidden 50 --latent-dim 128 --enc mtan_rnn --dec mtan_rnn --save 1 --classif --norm --learn-emb --k-iwae 1 --dataset mimiciii

Classification Task on MIMIC-III Dataset (mTAND-Full).log

wang67-jianli commented 1 year ago

Hi! How to get this: No such file or directory: '../../../neuraltimeseries/Dataset/final_input3.npy'?