sklearn.datasets.fetch_species_distributions

sklearn.datasets.fetch_species_distributions(data_home=None, download_if_missing=True) [source]

Loader for species distribution dataset from Phillips et. al. (2006)

Read more in the User Guide.

Parameters:

data_home : optional, default: None Specify another download and cache folder for the datasets. By default all scikit learn data is stored in ‘~/scikit_learn_data’ subfolders. download_if_missing: optional, True by default : If False, raise a IOError if the data is not locally available instead of trying to download the data from the source site.

Returns:

The data is returned as a Bunch object with the following attributes: : coverages : array, shape = [14, 1592, 1212] These represent the 14 features measured at each point of the map grid. The latitude/longitude values for the grid are discussed below. Missing data is represented by the value -9999. train : record array, shape = (1623,) The training points for the data. Each point has three fields: train[‘species’] is the species name train[‘dd long’] is the longitude, in degrees train[‘dd lat’] is the latitude, in degrees test : record array, shape = (619,) The test points for the data. Same format as the training data. Nx, Ny : integers The number of longitudes (x) and latitudes (y) in the grid x_left_lower_corner, y_left_lower_corner : floats The (x,y) position of the lower-left corner, in degrees grid_size : float The spacing between points of the grid, in degrees

Notes

• See examples/applications/plot_species_distribution_modeling.py for an example of using this dataset with scikit-learn

References

• “Maximum entropy modeling of species geographic distributions” S. J. Phillips, R. P. Anderson, R. E. Schapire - Ecological Modelling, 190:231-259, 2006.

Examples using sklearn.datasets.fetch_species_distributions