Stop using sklearn's private `_scorer` API for custom metrics in SKLL.

[desilinguist]

• Update scikit-learn to v1.3.0.
• Move all custom pre-defined metrics to _PREDEFINED_CUSTOM_METRICS dictionary in metrics.py.
• Make a copy of the above dictionary as CUSTOM _METRICS. This dictionary will be the source of all custom metrics: pre-defined and user-defined.
• We need two dictionaries because at some points in the code, we need to be able to differentiate between pre-defined custom metrics and user-defined custom metrics.
• Remove any use of sklearn.metrics._scorer private API and use sklearn.metrics.get_scorer() and sklearn.metrics.get_scorer_names() instead.
• Use the actual metric function when using custom metrics instead of its name. This is the core change that makes everything work since sklearn validates callables but does not validate custom metric name strings.
• Update tests to not use _SCORERS and fix a minor bug in another test related to scikit-learn v1.3.0.

This PR closes #748 and closes #750.

To review this PR, please try to create some custom metrics for both the titanic and California examples and try to use them via both the API and the configuration file.

[codecov[bot]]

Codecov Report

Patch coverage: 100.00% and project coverage change: +0.05 :tada:

Comparison is base (5fab3a5) 95.24% compared to head (075ab79) 95.30%.

Additional details and impacted files

```diff @@ Coverage Diff @@ ## main #751 +/- ## ========================================== + Coverage 95.24% 95.30% +0.05% ========================================== Files 29 29 Lines 3578 3576 -2 ========================================== Hits 3408 3408 + Misses 170 168 -2 ``` | [Impacted Files](https://app.codecov.io/gh/EducationalTestingService/skll/pull/751?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=EducationalTestingService) | Coverage Δ | | |---|---|---| | [skll/\_\_init\_\_.py](https://app.codecov.io/gh/EducationalTestingService/skll/pull/751?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=EducationalTestingService#diff-c2tsbC9fX2luaXRfXy5weQ==) | `100.00% <ø> (ø)` | | | [skll/data/writers.py](https://app.codecov.io/gh/EducationalTestingService/skll/pull/751?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=EducationalTestingService#diff-c2tsbC9kYXRhL3dyaXRlcnMucHk=) | `94.11% <ø> (+0.91%)` | :arrow_up: | | [skll/experiments/\_\_init\_\_.py](https://app.codecov.io/gh/EducationalTestingService/skll/pull/751?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=EducationalTestingService#diff-c2tsbC9leHBlcmltZW50cy9fX2luaXRfXy5weQ==) | `94.66% <100.00%> (-0.03%)` | :arrow_down: | | [skll/learner/\_\_init\_\_.py](https://app.codecov.io/gh/EducationalTestingService/skll/pull/751?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=EducationalTestingService#diff-c2tsbC9sZWFybmVyL19faW5pdF9fLnB5) | `97.19% <100.00%> (+<0.01%)` | :arrow_up: | | [skll/learner/utils.py](https://app.codecov.io/gh/EducationalTestingService/skll/pull/751?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=EducationalTestingService#diff-c2tsbC9sZWFybmVyL3V0aWxzLnB5) | `93.40% <100.00%> (+0.03%)` | :arrow_up: | | [skll/metrics.py](https://app.codecov.io/gh/EducationalTestingService/skll/pull/751?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=EducationalTestingService#diff-c2tsbC9tZXRyaWNzLnB5) | `97.16% <100.00%> (+0.08%)` | :arrow_up: |

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[mulhod]

Tests passed for me just now. Will review shortly.