Examples

Loading a dataset

# binary classification
import common_datasets.binary_classification as binclas

dataset = binclas.load_abalone19()

# multiclass classification
import common_datasets.multiclass_classification as multclas

dataset = multclas.load_abalone()

# regression
from common_datasets import regression

dataset = regression.load_treasury()

Querying all dataset loaders and loading a dataset

# binary classification
import common_datasets.binary_classification as binclas

data_loaders = binclas.get_data_loaders()

dataset_0 = data_loaders[0]()

# multiclass classification
import common_datasets.multiclass_classification as multclas

data_loaders = multclas.get_data_loaders()

dataset_0 = data_loaders[0]()

# regression
from common_datasets import regression

data_loaders = regression.get_data_loaders()

dataset_0 = data_loaders[0]()

Querying the loaders of the 5 smallest datasets regarding the total number of records

# binary classification
import common_datasets.binary_classification as binclas

data_loaders = binclas.get_filtered_data_loaders(n_smallest=5, sorting='n')

dataset_0 = data_loaders[0]()

# multiclass classification
import common_datasets.multiclass_classification as multclas

data_loaders = multclas.get_data_loaders(n_smallest=5, sorting='n')

dataset_0 = data_loaders[0]()

# regression
from common_datasets import regression

data_loaders = regression.get_data_loaders(n_smallest=5, sorting='n')

dataset_0 = data_loaders[0]()