FriedTiny

class capymoa.datasets.FriedTiny

Bases: _DownloadableARFF

A truncated version of the Friedman regression problem with 1000 instances.

This is a tiny version (1k instances) of the Fried dataset. This should only be used for quick tests, not for benchmarking algorithms.

See Fried for the full Friedman dataset.

__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