[BUG]: usage of camelcase for loss functions in `ml/incr/*`
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Mô tả
### Description
In continuation to this conversation [#13333](https://github.com/stdlib-js/stdlib/pull/13333#discussion_r3534668720), 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-huber`
- `squaredHinge` -> `squared-hinge`
`ml/incr/sgd-regression`
- `epsilonInsensitive` -> `epsilon-insensitive`
- `squaredError` -> `squared-error`
### Actual Results
```shell
```
### Version
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### Environments
Node.js
### Browser Version
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### Node.js / npm Version
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### Platform
_No response_
### Checklist
- [x] Read and understood the [Code of Conduct](https://github.com/stdlib-js/stdlib/blob/develop/CODE_OF_CONDUCT.md).
- [x] Searched for existing issues and pull requests.
Hướng dẫn đóng góp
Hướng nghiên cứu
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.
Do mô hình lập chỉ mục viết ra từ nội dung của issue.
Đánh giá
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- javascript
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- machine-learning
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- 2/5
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