[BUG]: usage of camelcase for loss functions in `ml/incr/*`
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Descripción
### 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
_No response_
### Questions
No.
### Demo
_No response_
### Reproduction
_No response_
### 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
_No response_
### Environments
Node.js
### Browser Version
_No response_
### Node.js / npm Version
_No response_
### 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.
Guía de contribución
Línea de trabajo
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.
Escrito por el modelo de indexación a partir del texto del issue.
Evaluación
- Stack tecnológico
- javascript
- Área
- machine-learning
- Tipo de issue
- Refactorización
- Dificultad
- 2/5
- Tiempo estimado
- 1-3 horas
- Estado de actividad
- Tranquilo
- Claridad
- Bien especificado
- Aptitud para principiantes
- 72/100