ucimlr.classification_datasets
all_datasets
all_datasets()
Returns a list of all ClassificationDataset classes.
Adult
class Adult(ClassificationDataset):
| Adult(root, split=TRAIN, validation_size=0.2)
Parameters
- root (
str
): Local path for storing/reading dataset files. - split (
str
): One of {'train', 'validation', 'test'} - validation_size (
float
): How large fraction in (0, 1) of the training partition to use for validation.
APSFailure
class APSFailure(ClassificationDataset):
| APSFailure(root, split=TRAIN, validation_size=0.2)
Parameters
- root (
str
): Local path for storing/reading dataset files. - split (
str
): One of {'train', 'validation', 'test'} - validation_size (
float
): How large fraction in (0, 1) of the training partition to use for validation.
Avila
class Avila(ClassificationDataset):
| Avila(root, split=TRAIN, validation_size=0.2)
Parameters
- root (
str
): Local path for storing/reading dataset files. - split (
str
): One of {'train', 'validation', 'test'} - validation_size (
float
): How large fraction in (0, 1) of the training partition to use for validation.
BankMarketing
class BankMarketing(ClassificationDataset):
| BankMarketing(root, split=TRAIN, validation_size=0.2)
Parameters
- root (
str
): Local path for storing/reading dataset files. - split (
str
): One of {'train', 'validation', 'test'} - validation_size (
float
): How large fraction in (0, 1) of the training partition to use for validation.
CardDefault
class CardDefault(ClassificationDataset):
| CardDefault(root, split=TRAIN, validation_size=0.2)
Parameters
- root (
str
): Local path for storing/reading dataset files. - split (
str
): One of {'train', 'validation', 'test'} - validation_size (
float
): How large fraction in (0, 1) of the training partition to use for validation.
Landsat
class Landsat(ClassificationDataset):
| Landsat(root, split=TRAIN, validation_size=0.2)
Parameters
- root (
str
): Local path for storing/reading dataset files. - split (
str
): One of {'train', 'validation', 'test'} - validation_size (
float
): How large fraction in (0, 1) of the training partition to use for validation.
LetterRecognition
class LetterRecognition(ClassificationDataset):
| LetterRecognition(root, split=TRAIN, validation_size=0.2)
Parameters
- root (
str
): Local path for storing/reading dataset files. - split (
str
): One of {'train', 'validation', 'test'} - validation_size (
float
): How large fraction in (0, 1) of the training partition to use for validation.
MagicGamma
class MagicGamma(ClassificationDataset):
| MagicGamma(root, split=TRAIN, validation_size=0.2)
Parameters
- root (
str
): Local path for storing/reading dataset files. - split (
str
): One of {'train', 'validation', 'test'} - validation_size (
float
): How large fraction in (0, 1) of the training partition to use for validation.
SensorLessDrive
class SensorLessDrive(ClassificationDataset):
| SensorLessDrive(root, split=TRAIN, validation_size=0.2)
Parameters
- root (
str
): Local path for storing/reading dataset files. - split (
str
): One of {'train', 'validation', 'test'} - validation_size (
float
): How large fraction in (0, 1) of the training partition to use for validation.
Shuttle
class Shuttle(ClassificationDataset):
| Shuttle(root, split=TRAIN, validation_size=0.2)
Description of dataset here.
Parameters
- root (
str
): Local path for storing/reading dataset files. - split (
str
): One of {'train', 'validation', 'test'} - validation_size (
float
): How large fraction in (0, 1) of the training partition to use for validation.