splitters

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iso_doc_type: "Specification" iso_viewpoint: "ComponentView" type: "module" title: "regression_model_template::utils::splitters — Dataset Partitioning Strategies" source_path: "src/regression_model_template/utils/splitters.py" description: "Abstract Splitter interface, TrainTestSplitter, and TimeSeriesSplitter partitioning datasets while respecting temporal order." tags: ["iso42010", "okf", "component_view", "splitters", "cross_validation"] timestamp: "2026-10-01T17:50:00Z" generated: "agent:wiki-iso-documentation-standard" verified: "true" last_verified_commit: "073b5fd"

regression_model_template::utils::splitters — Dataset Partitioning Strategies

Source: src/regression_model_template/utils/splitters.py (Lines: L1-L111)
Layer: Utilities
Role: Strategy abstraction partitioning tabular datasets into train and test splits, supporting random shuffling and strict temporal ordering.

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1. Class Diagram

classDiagram
    class Splitter {
        <<abstract>>
        +str KIND
        +split(inputs: Inputs, targets: Targets, groups: Index | None = None) TrainTestSplits*
        +get_n_splits(inputs: Inputs, targets: Targets, groups: Index | None = None) int*
    }

    class TrainTestSplitter {
        +str KIND = "TrainTestSplitter"
        +bool shuffle
        +int | float test_size
        +int random_state
        +split(inputs: Inputs, targets: Targets, groups: Index | None = None) TrainTestSplits
        +get_n_splits(inputs: Inputs, targets: Targets, groups: Index | None = None) int
    }
    TrainTestSplitter --|> Splitter : implements

    class TimeSeriesSplitter {
        +str KIND = "TimeSeriesSplitter"
        +int gap
        +int n_splits
        +int | float test_size
        +split(inputs: Inputs, targets: Targets, groups: Index | None = None) TrainTestSplits
        +get_n_splits(inputs: Inputs, targets: Targets, groups: Index | None = None) int
    }
    TimeSeriesSplitter --|> Splitter : implements

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