grakel.EdgeHistogram

class grakel.EdgeHistogram(n_jobs=None, normalize=False, verbose=False, sparse='auto')

Edge Histogram kernel as found in [SB15].

Parameters:

sparsebool, or ‘auto’, default=’auto’

Defines if the data will be stored in a sparse format. Sparse format is slower, but less memory consuming and in some cases the only solution. If ‘auto’, uses a sparse matrix when the number of zeros is more than the half of the matrix size. In all cases if the dense matrix doesn’t fit system memory, I sparse approach will be tried.

Attributes:

None.

Methods

diagonal()	Calculate the kernel matrix diagonal of the fitted data.
fit(X[, y])	Fit a dataset, for a transformer.
fit_transform(X[, y])	Fit and transform, on the same dataset.
get_metadata_routing()	Get metadata routing of this object.
get_params([deep])	Get parameters for this estimator.
initialize()	Initialize all transformer arguments, needing initialization.
pairwise_operation(x, y)	Calculate a pairwise kernel between two elements.
parse_input(X)	Parse and check the given input for EH kernel.
set_output(*[, transform])	Set output container.
set_params(**params)	Call the parent method.
transform(X)	Calculate the kernel matrix, between given and fitted dataset.

Initialize an edge kernel.

Attributes:

X

Methods

diagonal()	Calculate the kernel matrix diagonal of the fitted data.
fit(X[, y])	Fit a dataset, for a transformer.
fit_transform(X[, y])	Fit and transform, on the same dataset.
get_metadata_routing()	Get metadata routing of this object.
get_params([deep])	Get parameters for this estimator.
initialize()	Initialize all transformer arguments, needing initialization.
pairwise_operation(x, y)	Calculate a pairwise kernel between two elements.
parse_input(X)	Parse and check the given input for EH kernel.
set_output(*[, transform])	Set output container.
set_params(**params)	Call the parent method.
transform(X)	Calculate the kernel matrix, between given and fitted dataset.

__init__(n_jobs=None, normalize=False, verbose=False, sparse='auto')

Initialize an edge kernel.

Bibliography

[SB15]

Mahito Sugiyama and Karsten M. Borgwardt. Halting in Random Walk Kernels. In Advances in Neural Information Processing Systems, 1639–1647. 2015.