grakel.WeisfeilerLehman¶
- class grakel.WeisfeilerLehman(n_jobs=None, verbose=False, normalize=False, n_iter=5, base_graph_kernel=<class 'grakel.kernels.vertex_histogram.VertexHistogram'>)[source][source]¶
Compute the Weisfeiler Lehman Kernel.
See [SSVL+11].
- Parameters
- n_iterint, default=5
The number of iterations.
- base_graph_kernelgrakel.kernels.Kernel or tuple, default=None
If tuple it must consist of a valid kernel object and a dictionary of parameters. General parameters concerning normalization, concurrency, .. will be ignored, and the ones of given on __init__ will be passed in case it is needed. Default base_graph_kernel is VertexHistogram.
- Attributes
- Xdict
Holds a dictionary of fitted subkernel modules for all levels.
- _nxnumber
Holds the number of inputs.
- _n_iterint
Holds the number, of iterations.
- _base_graph_kernelfunction
A void function that initializes a base kernel object.
- _inv_labelsdict
An inverse dictionary, used for relabeling on each iteration.
Methods
diagonal()Calculate the kernel matrix diagonal for fitted data.
fit(X[, y])Fit a dataset, for a transformer.
fit_transform(X[, y])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 a pairwise kernel between two elements.
parse_input(X)Parse input for weisfeiler lehman.
set_params(**params)Call the parent method.
transform(X)Calculate the kernel matrix, between given and fitted dataset.
Initialise a weisfeiler_lehman kernel.
- Attributes
- X
Methods
diagonal()Calculate the kernel matrix diagonal for fitted data.
fit(X[, y])Fit a dataset, for a transformer.
fit_transform(X[, y])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 a pairwise kernel between two elements.
parse_input(X)Parse input for weisfeiler lehman.
set_params(**params)Call the parent method.
transform(X)Calculate the kernel matrix, between given and fitted dataset.
