CovtypeNorm#

class capymoa.datasets.CovtypeNorm[source]#

Bases: _DownloadableARFF

A normalized version of the classic Covtype classification problem.

Number of instances: 581,012 (30m^2 cells)
Number of attributes: 54 (10 continuous, 44 categorical)
Number of classes: 7 (forest cover types)

Forest Covertype (or simply covtype) contains the forest cover type for 30 x 30 meter cells obtained from US Forest Service (USFS) Region 2 Resource Information System (RIS) data.

References:

Blackard,Jock. (1998). Covertype. UCI Machine Learning Repository. https://doi.org/10.24432/C50K5N.
https://sourceforge.net/projects/moa-datastream/files/Datasets/Classification/covtypeNorm.arff.zip/download/

See Also:

CovtFD - Covtype with simulated feature drifts
Covtype - The classic covertype dataset
CovtypeTiny - A truncated version of the classic covertype dataset

__init__( directory: str | Path = get_download_dir(), auto_download: bool = True, )[source]#

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][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.

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

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

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.

classmethod to_stream(path: Path) → InstanceStream[source]#: Convert the downloaded and unpacked dataset into a datastream.

schema: Schema#

CovtypeNorm#

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