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