Manually setting the validation set for multi-output task

## Pull request overview

This pull request adds support for manually setting a validation set for multi-output tasks when using the "holdout" evaluation method. Previously, users could not manually specify a validation set for multi-output regression tasks. The new `multioutput_train_size` parameter allows users to concatenate training and validation data and specify where to split them.

**Changes:**
- Added `multioutput_train_size` parameter to AutoML class for manual validation set specification
- Implemented `_train_val_split` method to split concatenated training/validation data
- Added test case demonstrating the new functionality with MultiOutputRegressor

### Reviewed changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated 4 comments.

| File | Description |
| ---- | ----------- |
| flaml/automl/automl.py | Added documentation and implementation for the `multioutput_train_size` parameter, including the split logic in the `fit` method |
| test/automl/test_regression.py | Added `test_multioutput_train_size` function to demonstrate usage of the new feature |

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_Originally posted by @Copilot in https://github.com/microsoft/FLAML/pull/1302#pullrequestreview-3679883959_