peterlipan / asd_gp_gcn Goto Github PK
View Code? Open in Web Editor NEWASD diagnosis on ABIDE I
License: MIT License
ASD diagnosis on ABIDE I
License: MIT License
Great job! I used the commands
python download_ABIDE.py
python main.py
But I got the results:
GCN 10 fold test set results, loss = 0.691561, accuracy = 0.517241
GCN 10 fold val set results, loss = 0.632226, accuracy = 0.576923
Mean Accuracy: 0.522257
I haven't changed any parameters, and I would like to ask you if there might be other possible issues that are preventing me from replicating your results.
Excellent work,
I encountered an issue when running this line of code:
abide_dataset = TUDataset(args.data_dir, name='ABIDE', use_node_attr=True)
It results in an HTTP Error 404: Not Found.
Is this because the URL in the newer version of torch_geometric.datasets's TUDataset is incorrect? How can I resolve this problem?
Additionally, I'm curious to know why we need to download ABIDE.zip after data processing is already completed in construct_graph. What is the purpose of downloading this file?
Thank you very much for your explanation and assistance!
Hello, I am very interested in your work, but when I reproduce the code. The final result was
"GCN 10 fold test set results, loss = 0.777685, accuracy = 0.494253
GCN 10 fold val set results, Loss = 0.720890, accuracy = 0.589744
Mean Accuracy: 0.500562 ",
the TRAIN_ACC of MLP is 1.
Could you tell me what the problem is? Looking forward to your reply!
Traceback (most recent call last):
File "/download_ABIDE.py", line 83, in
brain_graph(logs, atlas, os.path.join(args.root, 'ABIDE', 'raw'), path)
File "/construct_graph.py", line 107, in brain_graph
cols = list(pd.read_csv(file_path, sep='\t').columns.values)
UnboundLocalError: local variable 'file_path' referenced before assignment
Great job!I have a little problem about the Graph pooling and LR. Does this LR classifier directly classifies downsample datas or deal with the features after GCN model? Could you share you source code about the Graph pooling and LR.I am looking forward to your answer.Thanks!
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.