grakel.PyramidMatch

class grakel.PyramidMatch(n_jobs=None, normalize=False, verbose=False, with_labels=True, L=4, d=6)

Pyramid match kernel class.

Kernel defined in [NMV17]

Parameters:

with_labelsbool, default=True

A flag that determines if the kernel computation will consider labels.

Lint, default=4

Pyramid histogram level.

dint, default=6

The dimension of the hypercube.

Attributes:

_num_labelsint

The number of distinct labels, on the fit data.

_labelsdict

A dictionary of label enumeration, made from fitted data.

Methods

diagonal()	Calculate the kernel matrix diagonal of the fit/transformed 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 create features for pyramid_match 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.

Initialise a pyramid_match kernel.

Attributes:

X

Methods

diagonal()	Calculate the kernel matrix diagonal of the fit/transformed 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 create features for pyramid_match 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, with_labels=True, L=4, d=6)

Initialise a pyramid_match kernel.

Bibliography

[NMV17]

Giannis Nikolentzos, Polykarpos Meladianos, and Michalis Vazirgiannis. Matching Node Embeddings for Graph Similarity. In Proceedings of the 31st AAAI Conference on Artificial Intelligence, 2429–2435. 2017.