def create(self, network_factory):
network = network_factory.create()
cluster = builder.try_get_node(network, "Cluster")
if cluster is None:
cluster = builder.create_cluster_variable(
network,
self._latent_states,
variable_name=self._latent_variable_name)
if not dk.empty(self._continuous):
for c_name in self._continuous.columns:
self._logger.info("Pre-processing {} column".format(c_name))
c = builder.create_continuous_variable(network, c_name)
try:
builder.create_link(network, cluster, c)
except ValueError as e:
self._logger.warn(e)
if not dk.empty(self._discrete):
for d_name in self._discrete.columns:
if d_name in self._discrete_states:
states = self._discrete_states[str(d_name)]
else:
states = dk.compute(self._discrete[str(
d_name)].dropna().unique()).tolist()
try:
c = builder.create_discrete_variable(
network, self._discrete, str(d_name), states)
builder.create_link(network, cluster, c)
except BaseException as e:
self._logger.warn(e)
return network
def create(self, network_factory):
network = network_factory.create()
if not dk.empty(self._continuous):
for c_name in self._continuous.columns:
c = builder.create_continuous_variable(network, c_name)
if dk.empty(self._discrete):
for d_name in self._discrete.columns:
if d_name in self._discrete_states:
states = self._discrete_states[d_name]
else:
states = dk.compute(
self._discrete[d_name].dropna().unique()).tolist()
try:
c = builder.create_discrete_variable(
network, self._discrete, d_name, states)
except BaseException as e:
self._logger.warn(e)
parent_node = builder.try_get_node(network, self._parent_node)
if parent_node is None:
raise ValueError("Parent node: {} not recognised".format(
self._parent_node))
for node in network.getNodes():
if node == parent_node:
continue
builder.create_link(network, parent_node, node)
return network
def create(self, network_factory: bayesianpy.network.NetworkFactory):
network = network_factory.create()
#builder.create_cluster_variable(network, 5)
if not dk.empty(self._continuous):
for c_name in self._continuous.columns:
builder.create_continuous_variable(network, c_name)
if not dk.empty(self._discrete):
for d_name in self._discrete.columns:
builder.create_discrete_variable(network, self._discrete, d_name, blanks=self._blanks)
network = bayesianpy.network.remove_single_state_nodes(network)
return network
def create(self, network_factory: bayesianpy.network.NetworkFactory):
network = network_factory.create()
cluster = builder.create_cluster_variable(network, self._latent_states)
if not dk.empty(self._continuous):
for c_name in self._continuous.columns:
c = builder.create_discretised_variable(network, self._continuous, c_name, bin_count=self._bin_count,
mode=self._binning_mode, zero_crossing=self._zero_crossing)
builder.create_link(network, cluster, c)
if not dk.empty(self._discrete):
for d_name in self._discrete.columns:
states = dk.compute(self._discrete[d_name].dropna().unique())
c = builder.create_discrete_variable(network, self._discrete, d_name, states)
builder.create_link(network, cluster, c)
return network