getml.datasets

The getml.datasets module includes utilities to load datasets, including methods to load and fetch popular reference datasets. It also features some artificial data generators.

Functions

load_air_pollution([roles, as_pandas])	Regression dataset on air pollution in Beijing, China
load_atherosclerosis([roles, as_pandas, as_dict])	Binary classification dataset on the lethality of atherosclerosis
load_biodegradability([roles, as_pandas, ...])	Regression dataset on molecule weight prediction
load_consumer_expenditures([roles, units, ...])	Binary classification dataset on consumer expenditures
load_interstate94([roles, units, as_pandas])	Regression dataset on traffic volume predicition
load_loans([roles, units, as_pandas, as_dict])	Binary classification dataset on loan default
load_occupancy([roles, as_pandas, as_dict])	Binary classification dataset on occupancy detection
make_categorical([n_rows_population, ...])	Generate a random dataset with categorical variables
make_discrete([n_rows_population, ...])	Generate a random dataset with categorical variables
make_numerical([n_rows_population, ...])	Generate a random dataset with continous numerical variables
make_same_units_categorical([...])	Generate a random dataset with categorical variables
make_same_units_numerical([...])	Generate a random dataset with continous numerical variables
make_snowflake([n_rows_population, ...])	Generate a random dataset with continous numerical variables