grakel.SubgraphMatching¶
- class grakel.SubgraphMatching(n_jobs=None, verbose=False, normalize=False, k=5, kv=<function _dirac>, ke=<function _dirac>, lw='uniform')[source][source]¶
Calculate the subgraph matching kernel.
See [KM12].
- Parameters
- kint, default=5
The upper bound for the maximum size of subgraphs.
- lwstr, valid_values={“uniform”, “increasing”, “decreasing”, “strong_decreasing”},
- default=”uniform” | iterable, size=k+1,
- | callable, num_of_arguments=1, argument_type=int
The lambda weights applied to the clique sizes.
- kvfunction (vertex_label, `vertex_label, -> number), or None
- default=:math:`k_{v}^{default}(l(a), l(b))= delta(l(a), l(b))`
The kernel function between two vertex_labels. If no function is provided, this is equivalent with not taking into account node labels.
- kefunction (edge_label, edge_label -> number),
- default=:math:`k_{e}^{default}(l(e), l(e’))= delta(l(e), l(e’))`
The kernel function between two edge_labels. If no function is provided, this is equivalent with not taking into account edge labels.
- Attributes
- lambdas_np.array, shape=(1, k+1)
All the lambdas corresponding to all the valid sizes of subgraphs.
Methods
diagonal()Calculate the kernel matrix diagonal of the fit/transformed data.
fit(X[, y])Fit a dataset, for a transformer.
fit_transform(X)Fit and transform, on the same dataset.
get_params([deep])Get parameters for this estimator.
initialize()Initialize all transformer arguments, needing initialization.
pairwise_operation(x, y)Calculate the subgraph_matching kernel.
parse_input(X)Parse and create features for the subgraph_matching kernel.
set_params(**params)Call the parent method.
transform(X)Calculate the kernel matrix, between given and fitted dataset.
Initialise a subgraph_matching 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)Fit and transform, on the same dataset.
get_params([deep])Get parameters for this estimator.
initialize()Initialize all transformer arguments, needing initialization.
pairwise_operation(x, y)Calculate the subgraph_matching kernel.
parse_input(X)Parse and create features for the subgraph_matching kernel.
set_params(**params)Call the parent method.
transform(X)Calculate the kernel matrix, between given and fitted dataset.