grakel.CoreFramework¶
- class grakel.CoreFramework(n_jobs=None, verbose=False, normalize=False, min_core=- 1, base_graph_kernel=None)[source][source]¶
The core kernel framework, as proposed in [NMLV18].
- Parameters
- 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.
- min_coreint, default=-1
Core numbers bigger than min_core will only be considered.
- Attributes
- base_graph_kernel_function
A void function that initializes a base kernel object.
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 and create features, while initializing and/or calculating sub-kernels.
set_params(**params)Call the parent method.
transform(X)Calculate the kernel matrix, between given and fitted dataset.
Initialise a hadamard_code 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 and create features, while initializing and/or calculating sub-kernels.
set_params(**params)Call the parent method.
transform(X)Calculate the kernel matrix, between given and fitted dataset.