Model Selection

• Hyper-parameter search methods
• Cross-validation splitting methods

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For validating models and performing hyper-parameter selection, it is common to use cross-validation methods such as those in sklearn.model_selection.

Although sklearn.model_selection is partially compatible with Sequentia, we define our own wrapped versions of certain classes and functions to allow support for sequences.

• Hyper-parameter search methods defines methods for searching hyper-parameter spaces in different ways, such as sequentia.model_selection.GridSearchCV.

• Cross-validation splitting methods defines methods for partitioning data into training/validation splits for cross-validation, such as sequentia.model_selection.KFold.