random_output_trees.datasets.fetch_drug_interaction¶

random_output_trees.datasets.fetch_drug_interaction(data_home=None)¶

Fetch the drug-interaction dataset

Constant features were removed.

Domain	drug-protein interaction network
Features	Biological (see [1])
output	interaction network
Drug matrix	(sample, features) = (1862, 660)
Newtork interaction matrix	(samples, labels) = (1862, 1554)

Parameters:

Parameters:	data_home: optional, default: None : Specify another download and cache folder for the data sets. By default all scikit learn data is stored in ‘~/scikit_learn_data’ subfolders.
Returns:	data : Bunch Dictionary-like object, the interesting attributes are: ‘data’, the data to learn, ‘target’, the classification labels, ‘target_names’, the original names of the target columns and ‘feature_names’, the original names of the dataset columns.

data_home: optional, default: None :

Specify another download and cache folder for the data sets. By default all scikit learn data is stored in ‘~/scikit_learn_data’ subfolders.

Returns:

data : Bunch

Dictionary-like object, the interesting attributes are: ‘data’, the data to learn, ‘target’, the classification labels, ‘target_names’, the original names of the target columns and ‘feature_names’, the original names of the dataset columns.

References

[R1]	Yamanishi, Y., Pauwels, E., Saigo, H., & Stoven, V. (2011). Extracting sets of chemical substructures and protein domains governing drug-target interactions. Journal of chemical information and modeling, 51(5), 1183-1194.