Accuracy

[shengaoya]

Accuracy

[peterlipan]

Hi! Thanks for your attention. I have rechecked and rerun my code and achieved the claimed performance. I need more information to find the possible problem. For example,

1. Have you implemented all the modules mentioned in our paper/code? e.g., Nested K-fold, modification on Hierarchical graph pooling, population graph construction.
2. Or, if you have run our code, could you please specify your modification on our settings? If all the parameters are unchanged, could you please provide the number of epochs of training GCN?

Thanks!

[shengaoya]

Hi！
First of all, I didn't change any code，But I downloaded the dataset myself. I downloaded 884 CPAC processed 'Rois_Ho' data and randomly selected 871 of them.And upload it to ./temp/ABIDE_pcp/cpac/filt_global.In the code:
the parameters of MLP is:
args.times = 3 # repeat times of the second level 10-fold cross-validation
args.least = 60 # smallest number of training epochs; avoid under-fitting
args.patience = 50 # patience for early stopping
args.epochs = 200 # maximum number of epochs
args.weight_decay = 0.1
args.nhid = 256

the parameters of GCN is:
args.num_features = args.nhid // 2 # output feature size of MLP
args.nhid = args.num_features // 2
args.epochs = 100000 # maximum number of training epochs
args.patience = 20000 # patience for early stop regarding the performance on val set
args.weight_decay = 0.001
args.least = 0 # least number of training epochs
In Addition，the 'lr' is 0.0001,'pooling_ratio' is 0.05,and 'dropout_ratio' is 0.01

But the final result was：
...
Training GCN on the 9 fold
Epoch: 021679 loss_train: 0.215433 acc_train: 0.922096 loss_val: 1.320118 acc_val: 0.576923 time: 348.476660s
Optimization Finished! Total time elapsed: 348.476696
GCN 09 fold test set results, loss = 0.853814, accuracy = 0.425287
GCN 09 fold val set results, loss = 0.768147, accuracy = 0.564103
Training GCN on the 10 fold
Epoch: 021788 loss_train: 0.201740 acc_train: 0.936261 loss_val: 0.995509 acc_val: 0.576923 time: 346.917461s
Optimization Finished! Total time elapsed: 346.917502
GCN 10 fold test set results, loss = 0.913977, accuracy = 0.494253
GCN 10 fold val set results, loss = 0.799268, accuracy = 0.525641

[peterlipan]

Hi! I am not sure if the data difference caused the problem, as some data cleaning exists in download_ABIDE.py. Could you please try the whole pipeline, using the same data, to check it? And, if possible, could you please provide your data, or info about how you downloaded it? I will try to test the model once I am free.

[shengaoya]

Hello, I downloaded it using the script on Github. How should I send the data to you? Could you please also send me your data? I couldn't download it by running the download_ABIDE. Py file. Looking forward to your reply！

[shengaoya]

If possible, my email is [email protected]

[peterlipan]

I have sent you the data via email. Please find enclosed for detail.

[peterlipan]

Hi! I received an email about this update of issue #3 but cannot find it on GitHub. The HTTPError is caused by the Great Firewall. To solve it, you may need a VPN. If this issue still exists, fill free to leave your email address so that I can send the dataset to you. Hope you can receive this reply.

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------------------ 原始邮件 ------------------ 发件人: "jhonP-Li/ASD_GP_GCN" ***@***.***>; 发送时间: 2022年6月29日(星期三) 晚上9:23 ***@***.***>; ***@***.***>;"State ***@***.***>; 主题: Re: [jhonP-Li/ASD_GP_GCN] Accuracy (Issue #3) Hello! The data I downloaded is also 884 samples! When I run the code, the 'abide_dataset = TUDataset(args.data_dir, name='ABIDE', use_node_attr=True)' in training.py report errors, i.e., urllib.error.HTTPError: HTTP Error 404: Not Found Can I download data directly and put it in a folder and skip this step — Reply to this email directly, view it on GitHub, or unsubscribe. You are receiving this because you modified the open/close state.Message ID: ***@***.***>