[BUG]: usage of camelcase for loss functions in `ml/incr/*`
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Assessment
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Newbie friendliness
- 72/100
- Issue type
- Refactor
- Clarity
- Clearly specified
- Activity status
- Quiet
- Tech stack
- javascript
- Domain
- machine-learning
Research direction
Start by inspecting the ml/incr/binary-classification and ml/incr/sgd-regression package entry points and searching their references for the four camelCase loss-function names. Rename each to its kebab-case form and verify that all package usage and tests consistently use modified-huber, squared-hinge, epsilon-insensitive, and squared-error.
Written by the indexing model from the issue text.
Description
Description
In continuation to this conversation #13333, we noticed that the packages ml/incr/binary-classification and ml/incr/sgd-regression follow camelCase for mentioning loss functions, where as the current convention is to use kebab-case.
Expected outcome is to refactor all the loss functions from using camelcase to kebabcase.
Related Issues
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Questions
No.
Demo
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Reproduction
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Expected Results
ml/incr/binary-classification
modifiedHuber->modified-hubersquaredHinge->squared-hinge
ml/incr/sgd-regression
epsilonInsensitive->epsilon-insensitivesquaredError->squared-error
Actual Results
Version
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Environments
Node.js
Browser Version
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Node.js / npm Version
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Platform
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Checklist
- Read and understood the Code of Conduct.
- Searched for existing issues and pull requests.
- Dominant language
- JavaScript
- Stars
- 6k
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- Avg merge
- 1d 4h
- Merged PRs (30d)
- 551
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.
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