def __repr__(self):
"""
Print a string description of the model when the model name is entered
in the terminal.
"""
width = 40
sections, section_titles = self._get_summary_struct()
accessible_fields = {
"cluster_id": "Cluster label for each row in the input dataset."
}
out = _toolkit_repr_print(self, sections, section_titles, width=width)
out2 = _summarize_accessible_fields(accessible_fields, width=width)
return out + "\n" + out2
def __repr__(self):
"""
Print a string description of the model when the model name is entered
in the terminal.
"""
width = 36
key_str = "{:<{}}: {}"
(sections, section_titles) = self._get_summary_struct()
accessible_fields = {
"entities": "Consolidated input records plus entity labels."}
out = _toolkit_repr_print(self, sections, section_titles, \
width=width)
out2 = _summarize_accessible_fields(accessible_fields, width=width)
return out + "\n" + out2
def __repr__(self):
"""
Return a string description of the model, including a description of
the training data, training statistics, and model hyper-parameters.
Returns
-------
out : string
A description of the model.
"""
accessible_fields = {
"vocabulary": "The vocabulary of the trimmed input."
}
(sections, section_titles) = self._get_summary_struct()
out = _toolkit_repr_print(self, sections, section_titles, width=30)
out2 = _summarize_accessible_fields(accessible_fields, width=30)
return out + "\n" + out2
def __repr__(self):
"""
Print a string description of the model when the model name is entered
in the terminal.
"""
width = 40
key_str = "{:<{}}: {}"
sections, section_titles = self._get_summary_struct()
accessible_fields = {
"scores": "Anomaly score for each instance in the current dataset."}
out = _tkutl._toolkit_repr_print(self, sections, section_titles,
width=width)
out2 = _summarize_accessible_fields(accessible_fields, width=width)
return out + "\n" + out2
def __repr__(self):
"""
Print a string description of the model when the model name is entered
in the terminal.
"""
width = 40
key_str = "{:<{}}: {}"
sections, section_titles = self._get_summary_struct()
accessible_fields = {
"scores": "Local outlier factor for each row in the input dataset.",
"nearest_neighbors_model": "Model used internally to compute nearest neighbors."}
out = _tkutl._toolkit_repr_print(self, sections, section_titles,
width=width)
out2 = _summarize_accessible_fields(accessible_fields, width=width)
return out + "\n" + out2
def __repr__(self):
"""
Print a string description of the model when the model name is entered
in the terminal.
"""
width = 36
sections, section_titles = self._get_summary_struct()
accessible_fields = {
"nearest_neighbors_model":
"Model used internally to compute nearest neighbors."
}
out = _tkutl._toolkit_repr_print(self,
sections,
section_titles,
width=width)
out2 = _summarize_accessible_fields(accessible_fields, width=width)
return out + "\n" + out2
def __repr__(self):
"""
Print a string description of the model when the model name is entered
in the terminal.
"""
width = 32
key_str = "{:<{}}: {}"
(sections, section_titles) = self._get_summary_struct()
accessible_fields = {
"cluster_id": "An SFrame containing the cluster assignments.",
"cluster_info": "An SFrame containing the cluster centers."}
out = _tkutl._toolkit_repr_print(self, sections, section_titles,
width=width)
out2 = _summarize_accessible_fields(accessible_fields, width=width)
return out + "\n" + out2