Bike#

class capymoa.datasets.Bike[source]#

Bases: DownloadARFFGzip

Bike is a regression dataset for the amount of bike share information.

  • Number of instances: 17,379

  • Number of attributes: 12

  • Number of targets: 1

This dataset contains the hourly and daily count of rental bikes between years 2011 and 2012 in Capital bike share system with the corresponding weather and seasonal information.

References: #. Fanaee-T, Hadi, and Joao Gama. “Event labeling combining ensemble detectors and background knowledge.” Progress in Artificial Intelligence 2 (2014): 113-127.

CLI_help() → str[source]#

Return cli help string for the stream.

__init__(
directory: str = PosixPath('data'),
auto_download: bool = True,
CLI: str | None = None,
schema: str | None = 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.

__iter__() → Iterator[_AnyInstance][source]#

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[source]#

Get the next instance in the stream.

Returns:

The next instance in the stream.

download(working_directory: Path) → Path[source]#

Download the dataset and return the path to the downloaded dataset within the working directory.

Parameters:

working_directory – The directory to download the dataset to.

Returns:

The path to the downloaded dataset within the working directory.

extract(stream_archive: Path) → Path[source]#

Extract the dataset from the archive and return the path to the extracted dataset.

Parameters:

stream_archive – The path to the archive containing the dataset.

Returns:

The path to the extracted dataset.

get_moa_stream() → InstanceStream | None[source]#

Get the MOA stream object if it exists.

get_path()[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() → _AnyInstance[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.

to_stream(stream: Path) → Any[source]#

Convert the dataset to a MOA stream.

Parameters:

stream – The path to the dataset.

Returns:

A MOA stream.