grakel.NeighborhoodHash#
- class grakel.NeighborhoodHash(n_jobs=None, normalize=False, verbose=False, random_state=None, R=3, nh_type='simple', bits=8)[source][source]#
Neighborhood hashing kernel as proposed in [HK09].
- Parameters:
- Rint, default=3
The maximum number of neighborhood hash.
- nh_typestr, valid_types={“simple”, “count_sensitive”}, default=”simple”
The existing neighborhood hash type as defined in [HK09].
- bytesint, default=2
Byte size of hashes.
- random_stateRandomState or int, default=None
A random number generator instance or an int to initialize a RandomState as a seed.
- Attributes:
- NH_function
The neighborhood hashing function.
- random_state_RandomState
A RandomState object handling all randomness of the class.
Methods
ROT(n, d)rot operation for binary numbers.
diagonal()Calculate the kernel matrix diagonal of the fit/transfromed 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.
neighborhood_hash_count_sensitive(G)Count sensitive neighborhood hash as defined in [HK09].
neighborhood_hash_simple(G)(simple) neighborhood hashing as defined in [HK09].
pairwise_operation(x, y)Calculate a pairwise kernel between two elements.
parse_input(X)Parse the given input and raise errors if it is invalid.
radix_sort_rot(labels)Sorts vertices based on labels.
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 a neighborhood_hash kernel.
- Attributes:
- X
Methods
ROT(n, d)rot operation for binary numbers.
diagonal()Calculate the kernel matrix diagonal of the fit/transfromed 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.
neighborhood_hash_count_sensitive(G)Count sensitive neighborhood hash as defined in [HK09].
neighborhood_hash_simple(G)(simple) neighborhood hashing as defined in [HK09].
pairwise_operation(x, y)Calculate a pairwise kernel between two elements.
parse_input(X)Parse the given input and raise errors if it is invalid.
radix_sort_rot(labels)Sorts vertices based on labels.
set_output(*[, transform])Set output container.
set_params(**params)Call the parent method.
transform(X)Calculate the kernel matrix, between given and fitted dataset.