Add character associated to each trial in P300 datasets
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- Dominant language
- Python
- Stars
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- Merged PRs (30d)
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Description
In P300 datasets, each trial is usually associated to a (binary) ERP class : target (target character has been flashed, evoking an ERP in the trial) versus non-target (target character has not been flashed, no ERP in trial).
But, we ignore the character class, ie the label of this target character, among all possible characters of the interface.
In P300 datasets, labels should contain:
- the ERP class for each trial;
- the list of flashed characters for each trial;
- the character class (ie, the target character) for each group of trials.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by locating the P300 dataset loading and label-generation entry points in the repository; no specific files or tests are named in the issue. Done means each trial exposes its ERP class and flashed-character list, while each trial group also exposes its target character class.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100