Feat sklearn pca50

[tonyliang19]

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[Copilot]

🟡 Changes recommended

The RandomizedSearchCV pipeline change will break hyperparameter search unless parameter names are prefixed/stripped correctly (and Y is made 1D), which currently is not handled.

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Pull request overview

This PR updates the sklearn method workflow/config to support iterating over multiple reduction modes (e.g., empty and pca50) and improves sklearn feature-selection training by standardizing features via a pipeline and expanding/aligning classifier definitions.

Changes:

• Run sklearn training across all values in params.sklearn_reduction (e.g., empty, pca50) instead of treating reduction as a single value.
• Update sklearn feature selection to scale features and adjust target shaping for estimator fitting.
• Refactor/extend sklearn classifier metadata in feature selection and align real_data.config with the canonical selectFeature parameter name.

File summaries

File	Description
subworkflows/methods/sklearn/main.nf	Iterates over all configured sklearn reduction modes via Channel.fromList.
modules/sklearn/select_feature/resources/usr/bin/sklearn_select_features.py	Adjusts final model fit target shaping.
modules/sklearn/select_feature/resources/usr/bin/run_random_search_cv.py	Switches RandomizedSearchCV to a StandardScaler+estimator pipeline.
modules/sklearn/select_feature/resources/usr/bin/load_classifier_class.py	Refactors classifier definitions and adds additional classifier options.
conf/real_data.config	Fixes profile param name to selectFeature.

Review details

• Files reviewed: 2/5 changed files
• Comments generated: 0
• Review effort level: Lite

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