Electricity

class capymoa.datasets.Electricity

Bases: _DownloadableARFF

Electricity is a classification problem based on the Australian New South Wales Electricity Market.

• Number of instances: 45,312

• Number of attributes: 8

• Number of classes: 2 (UP, DOWN)

The Electricity data set was collected from the Australian New South Wales Electricity Market, where prices are not fixed. It was described by M. Harries and analysed by Gama. These prices are affected by demand and supply of the market itself and set every five minutes. The Electricity data set contains 45,312 instances, where class labels identify the changes of the price (2 possible classes: up or down) relative to a moving average of the last 24 hours. An important aspect of this data set is that it exhibits temporal dependencies. This version of the dataset has been normalised (AKA elecNormNew) and it is the one most commonly used in benchmarks.

References:

1. https://sourceforge.net/projects/moa-datastream/files/Datasets/Classification/elecNormNew.arff.zip/download/

__init__(

directory: str | Path = get_download_dir(),

auto_download: bool = True,

)

Setup a stream from an ARFF 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.

__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 cli help string for the stream.

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() → _AnyInstance

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) → InstanceStream

Convert the downloaded and unpacked dataset into a datastream.

schema: Schema