streamsight.registries

Registry

Registry for algorithms, metrics and datasets. These registries are used to store the algorithms, metrics and datasets that are used in the experiments. The registries aid the programmer to keep track of valid classes and to easily instantiate them.

Contains the streamsight algorithms by default, and allows registration of new algorithms via the register function.

Example:

from streamsight.pipelines import ALGORITHM_REGISTRY
from streamsight.algorithms import ItemKNNStatic

algo = ALGORITHM_REGISTRY.get('ItemKNNStatic')(K=10)
ALGORITHM_REGISTRY.register('algo_1', ItemKNNStatic)

ALGORITHM_REGISTRY	Registry for easy retrieval of algorithm types by name.
DATASET_REGISTRY	Registry for easy retrieval of dataset types by name.
METRIC_REGISTRY	Registry for easy retrieval of metric types by name.
AlgorithmRegistry()	Registry for easy retrieval of algorithm types by name.
DatasetRegistry()	Registry for easy retrieval of dataset types by name.
MetricRegistry()	Registry for easy retrieval of metric types by name.

Entries

Entries for algorithms and metrics. These entries are used to store the algorithms and metrics in the registries. The entries are used to store the class and the parameters that are used to instantiate the class. These entires will be used in EvaluatorPipeline to instantiate the algorithms and metrics.

AlgorithmEntry(name[, params])	Entry for the algorithm registry.
MetricEntry(name[, K])	Entry for the metric registry.

Status Registry

Registry for algorithm status. This registry is used to store the status of the algorithms. The status of the algorithms are stored in the registry and can be accessed by the user. The status of the algorithms are used to keep track of the state of the algorithms.

AlgorithmStateEnum(value[, names, module, ...])	Enum for the state of the algorithm
AlgorithmStatusEntry(name, algo_id, state[, ...])	Entry for the algorithm status registry
AlgorithmStatusRegistry()	Registry for algorithm status.