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registries

Registries for algorithms, metrics, and datasets.

This module provides registries for storing and managing algorithms, metrics, and datasets used in experiments. Registries help keep track of valid classes and enable easy instantiation of components.

Registries

Registries store algorithms, metrics, and datasets by default and allow registration of new components via the register function.

Example: 

from recnexteval.pipelines import ALGORITHM_REGISTRY
from recnexteval.algorithms import ItemKNNStatic

algo = ALGORITHM_REGISTRY.get("ItemKNNStatic")(K=10)
ALGORITHM_REGISTRY.register(name="algo_1", algo_ptr=ItemKNNStatic)

Available Registries

  • ALGORITHM_REGISTRY: Registry for algorithms
  • DATASET_REGISTRY: Registry for datasets
  • METRIC_REGISTRY: Registry for metrics
  • AlgorithmRegistry: Class for creating algorithm registries
  • DatasetRegistry: Class for creating dataset registries
  • MetricRegistry: Class for creating metric registries

Entries

Entries store algorithms and metrics in registries. They maintain the class and parameters used to instantiate each component. These entries are used by EvaluatorPipeline to instantiate algorithms and metrics.

Available Entries

  • AlgorithmEntry: Entry for algorithms
  • MetricEntry: Entry for metrics