ElectricityTiny

class capymoa.datasets.ElectricityTiny

Bases: _DownloadableARFF

A truncated version of the Electricity dataset with 1000 instances.

This is a tiny version (2k instances) of the Electricity widely used dataset described by M. Harries. This should only be used for quick tests, not for benchmarking algorithms.

See Electricity for the widely used electricity dataset.

__init__(

directory: str | Path = get_download_dir(),

auto_download: bool = True,

file_type: Literal['arff', 'csv'] = 'arff',

)

Setup a stream from a dataset file and optionally download it if missing.

Parameters:

• directory – Where downloads are stored. Defaults to capymoa.datasets.get_download_dir().

• auto_download – Download the dataset if it is missing.

• file_type – Download either the "arff" or "csv" dataset asset.

__iter__() → Iterator[_AnyInstance]

Get an iterator over the stream.

This will NOT restart the stream if it has already been iterated over. Please use the restart() method to restart the stream.

Yield:

An iterator over the stream.

__next__() → _AnyInstance

Get the next instance in the stream.

Returns:

The next instance in the stream.

cli_help() → str

Return a help message

get_moa_stream() → InstanceStream | None

Get the MOA stream object if it exists.

get_schema() → Schema

Return the schema of the stream.

has_more_instances() → bool

Return True if the stream have more instances to read.

next_instance()

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()

Restart the stream to read instances from the beginning.

classmethod to_stream(path: Path) → Stream

Convert the downloaded and unpacked dataset into a datastream.

moa_stream: _InstanceStream | None

schema: Schema

stream: Stream