def hyperparameters(self):
'''A hierarchical representation of all the kernel hyperparameters.'''
return pretty_tuple('MarginalizedGraphKernel', [
'starting_probability', 'stopping_probability', 'node_kernel',
'edge_kernel'
])(self.p.theta, self.q, self.node_kernel.theta,
self.edge_kernel.theta)
def hyperparameter_bounds(self):
return pretty_tuple(
'Exponentiation',
['xi', 'kernel']
)(
self.xi_bounds, self.kernel.hyperparameter_bounds
)
def hyperparameter_bounds(self):
if self.s_bounds == "fixed":
return self.kernel.hyperparameter_bounds
else:
return pretty_tuple('GraphKernelHyperparameterBounds', [
'starting_probability', 'stopping_probability', 'node_kernel',
'edge_kernel', 'normalize_size'
])(self.kernel.p.bounds, self.kernel.q_bounds,
self.kernel.node_kernel.bounds, self.kernel.edge_kernel.bounds,
self.s_bounds)
def hyperparameters(self):
if self.s_bounds == "fixed":
return self.kernel.hyperparameters
else:
return pretty_tuple('MarginalizedGraphKernel', [
'starting_probability', 'stopping_probability', 'node_kernel',
'edge_kernel', 'normalize_size'
])(self.kernel.p.theta, self.kernel.q,
self.kernel.node_kernel.theta, self.kernel.edge_kernel.theta,
np.log(self.s))
def theta(self):
return pretty_tuple(self.name, ['h'])(self.h)
def theta(self):
return pretty_tuple(
self.name,
self._theta_values.keys()
)(**self._theta_values)
def theta(self):
return pretty_tuple(self.name, ['lhs', 'rhs'])(
self.k1.theta, self.k2.theta
)
def theta(self):
return pretty_tuple(self.name, self.kw_kernels.keys())(
*[k.theta for k in self.kw_kernels.values()])
def bounds(self):
return pretty_tuple(self.name, self.kw_kernels.keys())(
*[k.bounds for k in self.kw_kernels.values()])
def hyperparameter_bounds(self):
return pretty_tuple('GraphKernelHyperparameterBounds', [
'starting_probability', 'stopping_probability', 'node_kernel',
'edge_kernel'
])(self.p.bounds, self.q_bounds, self.node_kernel.bounds,
self.edge_kernel.bounds)
def hyperparameters(self):
return pretty_tuple('Kernel', ['v', 'L'])(self.v, self.L)
def theta(self):
return pretty_tuple(self.name, ['base'])(self.kernel.theta)
def hyperparameters(self):
return pretty_tuple('RBFKernel',
list(self._hyperparams.keys()) +
['distance'])(*self._hyperparams.values(),
self.distance.hyperparameters)
def theta(self):
return pretty_tuple('Uniform', ['p'])(self.p)