RecurrentConceptDriftStream#

class capymoa.stream.drift.RecurrentConceptDriftStream[source]#

Bases: DriftStream

CLI_help() → str[source]#: Return cli help string for the stream.

get_drifts()[source]#

get_moa_stream() → InstanceStream | None[source]#: Get the MOA stream object if it exists.

get_num_drifts()[source]#

get_schema() → Schema[source]#: Return the schema of the stream.

has_more_instances() → bool[source]#: Return True if the stream have more instances to read.

next_instance() → LabeledInstance | RegressionInstance[source]#

Return the next instance in the stream.

Raises:: ValueError – If the machine learning task is neither a regression nor a classification task.
Returns:: A labeled instances or a regression depending on the schema.

restart()[source]#: Restart the stream to read instances from the beginning.

__init__( concept_list: list, max_recurrences_per_concept: int = 3, transition_type_template: ~capymoa.stream.drift.Drift = <capymoa.stream.drift.AbruptDrift object>, concept_name_list: list = None, )[source]#

Construct a Stream from a MOA stream object.

Usually, you will want to construct a Stream using the capymoa.stream.stream_from_file() function.

Parameters:

moa_stream – The MOA stream object to read instances from. Is None if the stream is created from a numpy array.
schema – The schema of the stream. If None, the schema is inferred from the moa_stream.
CLI – Additional command line arguments to pass to the MOA stream.

Raises:

ValueError – If no schema is provided and no moa_stream is provided.
ValueError – If command line arguments are provided without a moa_stream.