class_docstr: Define a logistic regression classifier to evaluate the quality of embedding results
class_docstr_tok: ["Define","a","logistic","regression","classifier","to","evaluate","the","quality","of","embedding","results"]
code: def __init__(self, nfeat, nclass):
      super(LogisticRegressionClassifier, self).__init__()
      self.lrc = nn.Linear(nfeat, nclass)
  
file_path: dgl/examples/pytorch/rect/classify.py
imports: from statistics import mean
  import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 1 to create a new LogisticRegressionClassifier object from inherited base classes: nn with example: obj = LogisticRegressionClassifier(nfeat, nclass)