Comments (10)
You want to create a parallel folder.
Let's say you had one feature set in folder feature_one/:
feature_one/subject1/features.txt
feature_one/subject2/features.txt
feature_one/subject3/features.txt
feature_one/subject4/features.txt
You would want to create another folder feature_two:
feature_two/subject1/features.txt
feature_two/subject2/features.txt
feature_two/subject3/features.txt
feature_two/subject4/features.txt
and specify the two folder paths as multiple values for flag -u
-u /project/feature_one /project/feature_two
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Awesome :), thanks! Running now
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You want to name these top level folder appropriately, as they will be used to annotate the results. What kind of data are you using? and how long is neuropredict taking for each run?
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I'm examining subject scores from a two PLS analyses - one of vascular regions & a second of GM regions. I've run each of these separately (~ 15 min), but haven't looked at them together.
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A coffee break essentially :).. 15 mins has been typical in my experience also..
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Glad to hear youre able to use it. Spread the word! :)
I need to get a DOI somewhere so users can cite it..
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Sounds good! & I'm going to need to figure out how to report the results, so once I get through that, I may be able to help with documentation.
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That'd be awsome, John. Your help, being a new user, will be helpful for others. I may even use it automate that process further to minimize work for people later on.
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If predictive modeling is a non-trivial part of your study, I can help with completing the "analysis" and organizing reports as you need. If you just want to report some accuracy numbers and comparison, you probably wont need me.
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A reviewer argued that the PLS analysis we ran wasn't "novel enough", but that machine learning would be. Not trivial then. I'll take a first crack at this & send to you for vetting if that's ok. I want to make sure that what I say makes sense & accurately describes the results.
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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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