Comments (12)
It works now! Thanks :)
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Hi Pradeep!
I added the new argument, but I called it "nfeatures" because there is already a "num_features" variable in one of the functions that is defined in rhst.py.
Also, I changed the dtype in the metadata import command to "str" - this prevented the issue I was experiencing earlier when the subject list wasn't imported properly.
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Awsome! Can you check off the above to do list for the implementation and modify as necessary?
Before you make a pull request, I'd try testing it offline:
- with break points and print statements
- couple of runs with different values for actual data
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For sure! I'll copy the list here and edit this post because I'm not able to edit your initial post.
To do:
- add an argument: --num_features
- describe the argument thoroughly in help text
- checks on the input types
- checks on the input ranges
- checks on whether all the feature sets have the same number of features
- make the new argument interface with all the other methods, if need be.
- add option to pass on subset of feature names to visualize.feature_importance_map
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You don't need to edit the post, just need to tick the items off. I can tick off your todo list, hope you can do that with mine.
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Unfortunately I'm not able to edit it, but I think this might work:
- from https://github.com/raamana/neuropredict: Settings --> Collaborators --> search for amandakeasson
- from https://github.com/raamana/neuropredict/issues: click the checkbox to the left of the issue --> click "assign" --> hopefully my name appears and I'll be able to use your checklist :)
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Again, you don't need to edit it. Just mouse click on the radio button! Literally just click on it without editing it. This is not a big deal, just a way to track.
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Sorry, that's what I meant- that I'm not able to check off the boxes. I can check off the boxes on the checklist I copied into a new comment (i.e. without editing the post), but unfortunately I can't do the same for your checklist. Sorry for the confusion.
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Not a big deal at all. I added you as a collaborator now, may be that should help. Either way this is no big deal :)
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Hey Amanda, did you get time to work on this at all? I totally understand if you haven't been able to. Also, internal design changed a bit (actually a lot) when I tried to parallelize CV loop. Perhaps you can start from the new parallel version? Also I got some go at it for my use - you can use that? Let me know.
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I guess you’re probably too busy with research and haven’t gotten to github in awhile. I’ll close this for now. Reopen it when you have time to work on this. Thanks a lot for your help so far.
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Will do!
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Related Issues (20)
- Logging: Produce neuropredict own log
- Unable to launch multi-class classifier HOT 4
- Best options choice for classification of small and unbalanced dataset HOT 5
- Error when launching xgboost HOT 1
- Add new classifier: need of probability output? HOT 12
- Produce ROC curves for binary experiments HOT 1
- Show confidence intervals in the violin plots for BalACC, AUC etc
- List of subjects with high frequency of large residuals
- Make predictions in a new or held out dataset HOT 1
- Attribute-contrained performance estimates HOT 2
- update all docs and graphics to indicate users can try different models also HOT 1
- Classification blocked with multiple 1-dimensional features HOT 6
- Add docs for all API, esp. CVResults
- Allow user to use arbitrary Estimator via API
- ImportError: cannot import name 'MultiDatasetClassify' HOT 13
- Differences betw. frequency misclassified vs frequently correctly classified
- R version HOT 2
- Enabling plug-in user-chosen models or hyper-parameters
- Classify workflow Outputs - not displaying .csv HOT 3
- ENH: adopt more sophisticated hyper param opt toolboxes
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