Manually setting the validation set for multi-output task

[thinkall]

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 #1302 (review)