RBFm_100k

class capymoa.datasets.RBFm_100k

Bases: _DownloadableARFF

RBFm_100k is a synthetic classification problem based on the Radial Basis Function generator.

• Number of instances: 100,000

• Number of attributes: 10

• generators.RandomRBFGeneratorDrift -s 1.0E-4 -c 5

This is a snapshot (100k instances) of the synthetic generator RBF (Radial Basis Function), which works as follows: A fixed number of random centroids are generated. Each center has a random position, a single standard deviation, class label and weight. New examples are generated by selecting a center at random, taking weights into consideration so that centers with higher weight are more likely to be chosen. A random direction is chosen to offset the attribute values from the central point. The length of the displacement is randomly drawn from a Gaussian distribution with standard deviation determined by the chosen centroid. The chosen centroid also determines the class label of the example. This effectively creates a normally distributed hypersphere of examples surrounding each central point with varying densities. Only numeric attributes are generated.

__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